diff --git a/package.json b/package.json
index b8582407..f77a797e 100644
--- a/package.json
+++ b/package.json
@@ -124,6 +124,9 @@
     "typescript": "^4.5.4"
   },
   "jest": {
+    "testPathIgnorePatterns" : [
+      "<rootDir>/src/index.test.ts" 
+    ],
     "testEnvironment": "node",
     "preset": "ts-jest",
     "globals": {
diff --git a/src/cluster/kmeans.test.ts b/src/cluster/KMeans.test.ts
similarity index 98%
rename from src/cluster/kmeans.test.ts
rename to src/cluster/KMeans.test.ts
index 86388b19..6aa15ea9 100644
--- a/src/cluster/kmeans.test.ts
+++ b/src/cluster/KMeans.test.ts
@@ -1,4 +1,4 @@
-import { KMeans } from './kmeans'
+import { KMeans } from './KMeans'
 
 // Next steps: Improve on kmeans cluster testing
 describe('KMeans', () => {
@@ -40,7 +40,7 @@ describe('KMeans', () => {
 
   it('should save kmeans model', () => {
     const expectedResult = {
-      name: 'kmeans',
+      name: 'KMeans',
       nClusters: 2,
       init: 'random',
       maxIter: 300,
diff --git a/src/cluster/kmeans.ts b/src/cluster/KMeans.ts
similarity index 98%
rename from src/cluster/kmeans.ts
rename to src/cluster/KMeans.ts
index 09fb4c52..d5810cd1 100644
--- a/src/cluster/kmeans.ts
+++ b/src/cluster/KMeans.ts
@@ -71,7 +71,7 @@ export class KMeans extends Serialize {
   clusterCenters: tf.Tensor2D
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'kmeans'
+  name = 'KMeans'
 
   constructor({
     nClusters = 8,
@@ -145,7 +145,7 @@ export class KMeans extends Serialize {
   }
 
   /**
-   * Converts 2D input into a 1D Tensor which holds the Kmeans cluster Class label
+   * Converts 2D input into a 1D Tensor which holds the KMeans cluster Class label
    * @param X The 2D Matrix that you wish to cluster
    */
   public predict(X: Scikit2D): tf.Tensor1D {
diff --git a/src/compose/columnTransformer.test.ts b/src/compose/ColumnTransformer.test.ts
similarity index 79%
rename from src/compose/columnTransformer.test.ts
rename to src/compose/ColumnTransformer.test.ts
index a2506a0a..063da473 100644
--- a/src/compose/columnTransformer.test.ts
+++ b/src/compose/ColumnTransformer.test.ts
@@ -1,6 +1,6 @@
-import { ColumnTransformer } from './columnTransformer'
-import { MinMaxScaler } from '../preprocessing/minMaxScaler'
-import { SimpleImputer } from '../impute/simpleImputer'
+import { ColumnTransformer } from './ColumnTransformer'
+import { MinMaxScaler } from '../preprocessing/MinMaxScaler'
+import { SimpleImputer } from '../impute/SimpleImputer'
 import * as dfd from 'danfojs-node'
 
 describe('ColumnTransformer', function () {
diff --git a/src/compose/columnTransformer.ts b/src/compose/ColumnTransformer.ts
similarity index 99%
rename from src/compose/columnTransformer.ts
rename to src/compose/ColumnTransformer.ts
index d5f7200a..0f89059a 100644
--- a/src/compose/columnTransformer.ts
+++ b/src/compose/ColumnTransformer.ts
@@ -69,7 +69,7 @@ export class ColumnTransformer {
   remainder: Transformer | 'drop' | 'passthrough'
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'columntransformer'
+  name = 'ColumnTransformer'
 
   constructor({
     transformers = [],
diff --git a/src/dummy/dummyClassifier.test.ts b/src/dummy/DummyClassifier.test.ts
similarity index 95%
rename from src/dummy/dummyClassifier.test.ts
rename to src/dummy/DummyClassifier.test.ts
index fde16412..858c5adc 100644
--- a/src/dummy/dummyClassifier.test.ts
+++ b/src/dummy/DummyClassifier.test.ts
@@ -1,4 +1,4 @@
-import { DummyClassifier } from './dummyClassifier'
+import { DummyClassifier } from './DummyClassifier'
 
 describe('DummyClassifier', function () {
   it('Use DummyClassifier on simple example (mostFrequent)', function () {
@@ -62,7 +62,7 @@ describe('DummyClassifier', function () {
     ]
     const y = [10, 20, 20, 30]
     const expectedResult = {
-      name: 'dummyclassifier',
+      name: 'DummyClassifier',
       EstimatorType: 'classifier',
       constant: 20,
       strategy: 'mostFrequent',
diff --git a/src/dummy/dummyClassifier.ts b/src/dummy/DummyClassifier.ts
similarity index 99%
rename from src/dummy/dummyClassifier.ts
rename to src/dummy/DummyClassifier.ts
index bb76748d..c74a9a01 100644
--- a/src/dummy/dummyClassifier.ts
+++ b/src/dummy/DummyClassifier.ts
@@ -85,7 +85,7 @@ export class DummyClassifier extends ClassifierMixin {
   classes: number[] | string[]
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'dummyclassifier'
+  name = 'DummyClassifier'
 
   constructor({
     strategy = 'mostFrequent',
diff --git a/src/dummy/dummyRegressor.test.ts b/src/dummy/DummyRegressor.test.ts
similarity index 96%
rename from src/dummy/dummyRegressor.test.ts
rename to src/dummy/DummyRegressor.test.ts
index e88c9574..04299b7e 100644
--- a/src/dummy/dummyRegressor.test.ts
+++ b/src/dummy/DummyRegressor.test.ts
@@ -1,4 +1,4 @@
-import { DummyRegressor } from './dummyRegressor'
+import { DummyRegressor } from './DummyRegressor'
 
 describe('DummyRegressor', function () {
   it('Use DummyRegressor on simple example (mean)', function () {
@@ -65,7 +65,7 @@ describe('DummyRegressor', function () {
     ]
     const y = [10, 12, 30]
     const saveResult = {
-      name: 'dummyregressor',
+      name: 'DummyRegressor',
       EstimatorType: 'regressor',
       strategy: 'constant',
       constant: 10
diff --git a/src/dummy/dummyRegressor.ts b/src/dummy/DummyRegressor.ts
similarity index 99%
rename from src/dummy/dummyRegressor.ts
rename to src/dummy/DummyRegressor.ts
index c669b872..124b2249 100644
--- a/src/dummy/dummyRegressor.ts
+++ b/src/dummy/DummyRegressor.ts
@@ -84,7 +84,7 @@ export class DummyRegressor extends RegressorMixin {
   quantile?: number
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'dummyregressor'
+  name = 'DummyRegressor'
 
   constructor({
     strategy = 'mean',
diff --git a/src/ensemble/votingClassifier.test.ts b/src/ensemble/VotingClassifier.test.ts
similarity index 94%
rename from src/ensemble/votingClassifier.test.ts
rename to src/ensemble/VotingClassifier.test.ts
index 69e2eb92..d741c00a 100644
--- a/src/ensemble/votingClassifier.test.ts
+++ b/src/ensemble/VotingClassifier.test.ts
@@ -1,7 +1,7 @@
-import { makeVotingClassifier, VotingClassifier } from './votingClassifier'
-import { DummyClassifier } from '../dummy/dummyClassifier'
+import { makeVotingClassifier, VotingClassifier } from './VotingClassifier'
+import { DummyClassifier } from '../dummy/DummyClassifier'
 
-import { LogisticRegression } from '../linear_model/logisticRegression'
+import { LogisticRegression } from '../linear_model/LogisticRegression'
 
 describe('VotingClassifier', function () {
   it('Use VotingClassifier on simple example (voting = hard)', async function () {
diff --git a/src/ensemble/votingClassifier.ts b/src/ensemble/VotingClassifier.ts
similarity index 98%
rename from src/ensemble/votingClassifier.ts
rename to src/ensemble/VotingClassifier.ts
index 35d92853..5db1241e 100644
--- a/src/ensemble/votingClassifier.ts
+++ b/src/ensemble/VotingClassifier.ts
@@ -1,7 +1,7 @@
 import { Scikit1D, Scikit2D } from '../types'
 import { tf } from '../shared/globals'
 import { ClassifierMixin } from '../mixins'
-import { LabelEncoder } from '../preprocessing/labelEncoder'
+import { LabelEncoder } from '../preprocessing/LabelEncoder'
 import { fromJson, toJson } from './serializeEnsemble'
 
 /*
diff --git a/src/ensemble/votingRegressor.test.ts b/src/ensemble/VotingRegressor.test.ts
similarity index 87%
rename from src/ensemble/votingRegressor.test.ts
rename to src/ensemble/VotingRegressor.test.ts
index 6421670e..06a69f97 100644
--- a/src/ensemble/votingRegressor.test.ts
+++ b/src/ensemble/VotingRegressor.test.ts
@@ -1,6 +1,6 @@
-import { makeVotingRegressor, VotingRegressor } from './votingRegressor'
-import { DummyRegressor } from '../dummy/dummyRegressor'
-import { LinearRegression } from '../linear_model/linearRegression'
+import { makeVotingRegressor, VotingRegressor } from './VotingRegressor'
+import { DummyRegressor } from '../dummy/DummyRegressor'
+import { LinearRegression } from '../linear_model/LinearRegression'
 
 describe('VotingRegressor', function () {
   it('Use VotingRegressor on simple example ', async function () {
diff --git a/src/ensemble/votingRegressor.ts b/src/ensemble/VotingRegressor.ts
similarity index 100%
rename from src/ensemble/votingRegressor.ts
rename to src/ensemble/VotingRegressor.ts
diff --git a/src/ensemble/serializeEnsemble.ts b/src/ensemble/serializeEnsemble.ts
index b148ed97..245c89df 100644
--- a/src/ensemble/serializeEnsemble.ts
+++ b/src/ensemble/serializeEnsemble.ts
@@ -1,34 +1,34 @@
-import { DummyClassifier } from '../dummy/dummyClassifier'
-import { DummyRegressor } from '../dummy/dummyRegressor'
-import { LogisticRegression } from '../linear_model/logisticRegression'
-import { RidgeRegression } from '../linear_model/ridgeRegression'
-import { LinearRegression } from '../linear_model/linearRegression'
-import { LassoRegression } from '../linear_model/lassoRegression'
-import { ElasticNet } from '../linear_model/elasticNet'
-import { LabelEncoder } from '../preprocessing/labelEncoder'
-import { SimpleImputer } from '../impute/simpleImputer'
+import { DummyClassifier } from '../dummy/DummyClassifier'
+import { DummyRegressor } from '../dummy/DummyRegressor'
+import { LogisticRegression } from '../linear_model/LogisticRegression'
+import { RidgeRegression } from '../linear_model/RidgeRegression'
+import { LinearRegression } from '../linear_model/LinearRegression'
+import { LassoRegression } from '../linear_model/LassoRegression'
+import { ElasticNet } from '../linear_model/ElasticNet'
+import { LabelEncoder } from '../preprocessing/LabelEncoder'
+import { SimpleImputer } from '../impute/SimpleImputer'
 import { tf } from '../shared/globals'
-import { MinMaxScaler } from '../preprocessing/minMaxScaler'
+import { MinMaxScaler } from '../preprocessing/MinMaxScaler'
 
 function getEstimator(name: string, serialJson: string) {
   switch (name) {
-    case 'dummyclassifier':
+    case 'DummyClassifier':
       return new DummyClassifier().fromJson(serialJson)
-    case 'dummyregressor':
+    case 'DummyRegressor':
       return new DummyRegressor().fromJson(serialJson)
-    case 'logisticregression':
+    case 'LogisticRegression':
       return new LogisticRegression().fromJson(serialJson)
-    case 'ridgeregression':
+    case 'RidgeRegression':
       return new RidgeRegression().fromJson(serialJson)
-    case 'linearregression':
+    case 'LinearRegression':
       return new LinearRegression().fromJson(serialJson)
-    case 'lassoregression':
+    case 'LassoRegression':
       return new LassoRegression().fromJson(serialJson)
-    case 'elasticnet':
+    case 'ElasticNet':
       return new ElasticNet().fromJson(serialJson)
-    case 'simpleimputer':
+    case 'SimpleImputer':
       return new SimpleImputer().fromJson(serialJson)
-    case 'minmaxscaler':
+    case 'MinMaxScaler':
       return new MinMaxScaler().fromJson(serialJson)
     default:
       throw new Error(`${name} estimator not supported`)
diff --git a/src/impute/simpleImputer.test.ts b/src/impute/SimpleImputer.test.ts
similarity index 98%
rename from src/impute/simpleImputer.test.ts
rename to src/impute/SimpleImputer.test.ts
index 9a861d2f..fb58af50 100644
--- a/src/impute/simpleImputer.test.ts
+++ b/src/impute/SimpleImputer.test.ts
@@ -1,5 +1,5 @@
 import { tf } from '../shared/globals'
-import { SimpleImputer } from './simpleImputer'
+import { SimpleImputer } from './SimpleImputer'
 
 describe('SimpleImputer', function () {
   it('Imputes with "constant" strategy 2D one column. In this strategy, we give the fill value', function () {
@@ -131,7 +131,7 @@ describe('SimpleImputer', function () {
     ]
 
     const expected = {
-      name: 'simpleimputer',
+      name: 'SimpleImputer',
       missingValues: null,
       strategy: 'mostFrequent',
       statistics: {
diff --git a/src/impute/simpleImputer.ts b/src/impute/SimpleImputer.ts
similarity index 99%
rename from src/impute/simpleImputer.ts
rename to src/impute/SimpleImputer.ts
index cf5de91d..722591c7 100644
--- a/src/impute/simpleImputer.ts
+++ b/src/impute/SimpleImputer.ts
@@ -66,7 +66,7 @@ export class SimpleImputer extends TransformerMixin {
   statistics: tf.Tensor1D
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'simpleimputer'
+  name = 'SimpleImputer'
 
   constructor({
     strategy = 'mean',
diff --git a/src/index.test.ts b/src/index.test.ts
index bf1e606e..eb1f7291 100644
--- a/src/index.test.ts
+++ b/src/index.test.ts
@@ -1,18 +1,18 @@
-import './cluster/kmeans.test'
-import './compose/columnTransformer.test'
+import './cluster/KMeans.test'
+import './compose/ColumnTransformer.test'
 import './datasets/makeRegression.test'
-import './dummy/dummyClassifier.test'
-import './dummy/dummyRegressor.test'
-import './ensemble/votingClassifier.test'
-import './ensemble/votingRegressor.test'
-import './impute/simpleImputer.test'
-import './linear_model/linearRegression.test'
+import './dummy/DummyClassifier.test'
+import './dummy/DummyRegressor.test'
+import './ensemble/VotingClassifier.test'
+import './ensemble/VotingRegressor.test'
+import './impute/SimpleImputer.test'
+import './linear_model/LinearRegression.test'
 /* When we figure out why we can't save / load logistic regressions */
 // import './linear_model/logisticRegression.test'
 import './metrics/metrics.test'
-// import './model_selection/kFold.test'
+// import './model_selection/KFold.test'
 import './model_selection/trainTestSplit.test'
-import './naive_bayes/gaussianNaiveBayes.test'
+import './naive_bayes/GaussianNB.test'
 /* When we figure out how to do expect.extend in karma */
 // import './neighbors/bruteNeighborhood.test'
 // import './neighbors/cappedMaxHeap.test'
@@ -20,22 +20,22 @@ import './naive_bayes/gaussianNaiveBayes.test'
 // import './neighbors/kNeighborsClassifier.test'
 // import './neighbors/kNeighborsRegressor.test'
 // import './neighbors/metrics.test'
-import './pipeline/pipeline.test'
-import './preprocessing/labelEncoder.test'
-import './preprocessing/maxAbsScaler.test'
-import './preprocessing/minMaxScaler.test'
-import './preprocessing/normalizer.test'
-import './preprocessing/oneHotEncoder.test'
-import './preprocessing/ordinalEncoder.test'
-import './preprocessing/robustScaler.test'
-import './preprocessing/standardScaler.test'
-import './svm/linearSVC.test'
-import './svm/linearSVR.test'
+import './pipeline/Pipeline.test'
+import './preprocessing/LabelEncoder.test'
+import './preprocessing/MaxAbsScaler.test'
+import './preprocessing/MinMaxScaler.test'
+import './preprocessing/Normalizer.test'
+import './preprocessing/OneHotEncoder.test'
+import './preprocessing/OrdinalEncoder.test'
+import './preprocessing/RobustScaler.test'
+import './preprocessing/StandardScaler.test'
+import './svm/LinearSVC.test'
+import './svm/LinearSVR.test'
 /* When we put back in the SVM code */
 // import './svm/SVC.test'
 // import './svm/SVR.test'
-import './tree/criterion.test'
-// import './tree/decisiontree.test'
-import './tree/splitter.test'
+import './tree/Criterion.test'
+// import './tree/DecisionTree.test'
+import './tree/Splitter.test'
 /* When we use the expect.extend stuff */
 // import './jestTensorMatchers.test'
diff --git a/src/index.ts b/src/index.ts
index 69172976..6ab8fb07 100644
--- a/src/index.ts
+++ b/src/index.ts
@@ -12,74 +12,74 @@
 * limitations under the License.
 * ==========================================================================
 */
-export { KNeighborsRegressor } from './neighbors/kNeighborsRegressor'
+export { KNeighborsRegressor } from './neighbors/KNeighborsRegressor'
 export {
   LinearRegression,
   LinearRegressionParams
-} from './linear_model/linearRegression'
-export { LassoRegression, LassoParams } from './linear_model/lassoRegression'
+} from './linear_model/LinearRegression'
+export { LassoRegression, LassoParams } from './linear_model/LassoRegression'
 export {
   RidgeRegression,
   RidgeRegressionParams
-} from './linear_model/ridgeRegression'
-export { ElasticNet, ElasticNetParams } from './linear_model/elasticNet'
+} from './linear_model/RidgeRegression'
+export { ElasticNet, ElasticNetParams } from './linear_model/ElasticNet'
 export {
   LogisticRegression,
   LogisticRegressionParams
-} from './linear_model/logisticRegression'
+} from './linear_model/LogisticRegression'
 export * as metrics from './metrics/metrics'
-export { DummyRegressor, DummyRegressorParams } from './dummy/dummyRegressor'
+export { DummyRegressor, DummyRegressorParams } from './dummy/DummyRegressor'
 export {
   DummyClassifier,
   DummyClassifierParams
-} from './dummy/dummyClassifier'
-export { MinMaxScaler, MinMaxScalerParams } from './preprocessing/minMaxScaler'
+} from './dummy/DummyClassifier'
+export { MinMaxScaler, MinMaxScalerParams } from './preprocessing/MinMaxScaler'
 export {
   StandardScaler,
   StandardScalerParams
-} from './preprocessing/standardScaler'
-export { MaxAbsScaler } from './preprocessing/maxAbsScaler'
-export { SimpleImputer, SimpleImputerParams } from './impute/simpleImputer'
+} from './preprocessing/StandardScaler'
+export { MaxAbsScaler } from './preprocessing/MaxAbsScaler'
+export { SimpleImputer, SimpleImputerParams } from './impute/SimpleImputer'
 export {
   OneHotEncoder,
   OneHotEncoderParams
-} from './preprocessing/oneHotEncoder'
-export { LabelEncoder } from './preprocessing/labelEncoder'
+} from './preprocessing/OneHotEncoder'
+export { LabelEncoder } from './preprocessing/LabelEncoder'
 export {
   OrdinalEncoder,
   OrdinalEncoderParams
-} from './preprocessing/ordinalEncoder'
-export { Normalizer, NormalizerParams } from './preprocessing/normalizer'
-export { Pipeline, PipelineParams, makePipeline } from './pipeline/pipeline'
+} from './preprocessing/OrdinalEncoder'
+export { Normalizer, NormalizerParams } from './preprocessing/Normalizer'
+export { Pipeline, PipelineParams, makePipeline } from './pipeline/Pipeline'
 export {
   ColumnTransformer,
   ColumnTransformerParams
-} from './compose/columnTransformer'
-export { RobustScaler, RobustScalerParams } from './preprocessing/robustScaler'
-export { KMeans, KMeansParams } from './cluster/kmeans'
+} from './compose/ColumnTransformer'
+export { RobustScaler, RobustScalerParams } from './preprocessing/RobustScaler'
+export { KMeans, KMeansParams } from './cluster/KMeans'
 export { Scikit1D, Scikit2D, ScikitVecOrMatrix } from './types'
 export { dataUrls } from './datasets/datasets'
 export {
   makeVotingRegressor,
   VotingRegressor,
   VotingRegressorParams
-} from './ensemble/votingRegressor'
+} from './ensemble/VotingRegressor'
 export {
   makeVotingClassifier,
   VotingClassifier,
   VotingClassifierParams
-} from './ensemble/votingClassifier'
-export { LinearSVC, LinearSVCParams } from './svm/linearSVC'
-export { LinearSVR, LinearSVRParams } from './svm/linearSVR'
+} from './ensemble/VotingClassifier'
+export { LinearSVC, LinearSVCParams } from './svm/LinearSVC'
+export { LinearSVR, LinearSVRParams } from './svm/LinearSVR'
 
 // Comment these out until our libsvm version doesn't ship with fs / path subdependencies
 // They were stopping the browser build from being built
 // export { SVR, SVRParams } from './svm/SVR'
 // export { SVC, SVCParams } from './svm/SVC'
-export { GaussianNB } from './naive_bayes/gaussianNaiveBayes'
+export { GaussianNB } from './naive_bayes/GaussianNB'
 export {
   DecisionTreeClassifier,
   DecisionTreeClassifierParams,
   DecisionTreeRegressor,
   DecisionTreeRegressorParams
-} from './tree/decisiontree'
+} from './tree/DecisionTree'
diff --git a/src/linear_model/elasticNet.ts b/src/linear_model/ElasticNet.ts
similarity index 96%
rename from src/linear_model/elasticNet.ts
rename to src/linear_model/ElasticNet.ts
index 53cbae7e..a35f35b6 100644
--- a/src/linear_model/elasticNet.ts
+++ b/src/linear_model/ElasticNet.ts
@@ -13,7 +13,7 @@
 * ==========================================================================
 */
 
-import { SGDRegressor } from './sgdRegressor'
+import { SGDRegressor } from './SgdRegressor'
 import { tf } from '../shared/globals'
 
 // First pass at a ElasticNet implementation using gradient descent
@@ -34,7 +34,7 @@ export interface ElasticNetParams {
  */
 export class ElasticNet extends SGDRegressor {
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'elasticnet'
+  name = 'ElasticNet'
 
   constructor({
     alpha = 1,
diff --git a/src/linear_model/lassoRegression.ts b/src/linear_model/LassoRegression.ts
similarity index 96%
rename from src/linear_model/lassoRegression.ts
rename to src/linear_model/LassoRegression.ts
index a6ccba5b..32f1438c 100644
--- a/src/linear_model/lassoRegression.ts
+++ b/src/linear_model/LassoRegression.ts
@@ -13,7 +13,7 @@
 * ==========================================================================
 */
 
-import { SGDRegressor } from './sgdRegressor'
+import { SGDRegressor } from './SgdRegressor'
 import { tf } from '../shared/globals'
 
 // First pass at a LassoRegression implementation using gradient descent
@@ -29,7 +29,7 @@ export interface LassoParams {
 /** Linear Model trained with L1 prior as regularizer (aka the Lasso). */
 export class LassoRegression extends SGDRegressor {
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'lassoregression'
+  name = 'LassoRegression'
 
   constructor({ fitIntercept = true, alpha = 1.0 }: LassoParams = {}) {
     super({
diff --git a/src/linear_model/linearRegression.test.ts b/src/linear_model/LinearRegression.test.ts
similarity index 98%
rename from src/linear_model/linearRegression.test.ts
rename to src/linear_model/LinearRegression.test.ts
index 14787922..a4d67295 100644
--- a/src/linear_model/linearRegression.test.ts
+++ b/src/linear_model/LinearRegression.test.ts
@@ -1,4 +1,4 @@
-import { LinearRegression } from './linearRegression'
+import { LinearRegression } from './LinearRegression'
 import { tensorEqual } from '../utils'
 import { tf } from '../shared/globals'
 
diff --git a/src/linear_model/linearRegression.ts b/src/linear_model/LinearRegression.ts
similarity index 97%
rename from src/linear_model/linearRegression.ts
rename to src/linear_model/LinearRegression.ts
index 184a4183..3c4e099c 100644
--- a/src/linear_model/linearRegression.ts
+++ b/src/linear_model/LinearRegression.ts
@@ -13,7 +13,7 @@
 * ==========================================================================
 */
 
-import { SGDRegressor } from './sgdRegressor'
+import { SGDRegressor } from './SgdRegressor'
 import { tf } from '../shared/globals'
 
 /**
@@ -67,7 +67,7 @@ Next steps:
  */
 export class LinearRegression extends SGDRegressor {
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'linearregression'
+  name = 'LinearRegression'
 
   constructor({ fitIntercept = true }: LinearRegressionParams = {}) {
     super({
diff --git a/src/linear_model/logisticRegression.test.ts b/src/linear_model/LogisticRegression.test.ts
similarity index 98%
rename from src/linear_model/logisticRegression.test.ts
rename to src/linear_model/LogisticRegression.test.ts
index ba8ca88a..c00db0fa 100644
--- a/src/linear_model/logisticRegression.test.ts
+++ b/src/linear_model/LogisticRegression.test.ts
@@ -1,4 +1,4 @@
-import { LogisticRegression } from './logisticRegression'
+import { LogisticRegression } from './LogisticRegression'
 import { tf } from '../shared/globals'
 
 describe('LogisticRegression', function () {
diff --git a/src/linear_model/logisticRegression.ts b/src/linear_model/LogisticRegression.ts
similarity index 97%
rename from src/linear_model/logisticRegression.ts
rename to src/linear_model/LogisticRegression.ts
index b873fb9e..30651225 100644
--- a/src/linear_model/logisticRegression.ts
+++ b/src/linear_model/LogisticRegression.ts
@@ -13,7 +13,7 @@
 // * ==========================================================================
 // */
 
-import { SGDClassifier } from './sgdClassifier'
+import { SGDClassifier } from './SgdClassifier'
 import { tf } from '../shared/globals'
 
 // First pass at a LogisticRegression implementation using gradient descent
@@ -61,7 +61,7 @@ export interface LogisticRegressionParams {
 */
 export class LogisticRegression extends SGDClassifier {
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'logisticregression'
+  name = 'LogisticRegression'
 
   constructor({
     penalty = 'l2',
diff --git a/src/linear_model/ridgeRegression.ts b/src/linear_model/RidgeRegression.ts
similarity index 96%
rename from src/linear_model/ridgeRegression.ts
rename to src/linear_model/RidgeRegression.ts
index 24e9c1b8..1d3cbf72 100644
--- a/src/linear_model/ridgeRegression.ts
+++ b/src/linear_model/RidgeRegression.ts
@@ -13,7 +13,7 @@
 * ==========================================================================
 */
 
-import { SGDRegressor } from './sgdRegressor'
+import { SGDRegressor } from './SgdRegressor'
 import { tf } from '../shared/globals'
 
 // RidgeRegression implementation using gradient descent
@@ -31,7 +31,7 @@ export interface RidgeRegressionParams {
 /** Linear least squares with l2 regularization. */
 export class RidgeRegression extends SGDRegressor {
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'ridgeregression'
+  name = 'RidgeRegression'
 
   constructor({
     fitIntercept = true,
diff --git a/src/linear_model/sgdClassifier.ts b/src/linear_model/SgdClassifier.ts
similarity index 99%
rename from src/linear_model/sgdClassifier.ts
rename to src/linear_model/SgdClassifier.ts
index ac48fe78..b5900a39 100644
--- a/src/linear_model/sgdClassifier.ts
+++ b/src/linear_model/SgdClassifier.ts
@@ -17,7 +17,7 @@ import { tf } from '../shared/globals'
 // import { DenseLayerArgs } from '@tensorflow/tfjs-layers/dist/layers/core'
 import { convertToNumericTensor1D, convertToNumericTensor2D } from '../utils'
 import { Scikit2D, Scikit1D, OptimizerTypes, LossTypes } from '../types'
-import { OneHotEncoder } from '../preprocessing/oneHotEncoder'
+import { OneHotEncoder } from '../preprocessing/OneHotEncoder'
 import { assert } from '../typesUtils'
 import { ClassifierMixin } from '../mixins'
 import { fromJson, toJSON } from './modelSerializer'
diff --git a/src/linear_model/sgdRegressor.ts b/src/linear_model/SgdRegressor.ts
similarity index 100%
rename from src/linear_model/sgdRegressor.ts
rename to src/linear_model/SgdRegressor.ts
diff --git a/src/linear_model/modelSerializer.ts b/src/linear_model/modelSerializer.ts
index 703f8328..aac0aeba 100644
--- a/src/linear_model/modelSerializer.ts
+++ b/src/linear_model/modelSerializer.ts
@@ -1,6 +1,6 @@
 import { optimizer, initializer, getLoss } from '../utils'
 import { tf } from '../shared/globals'
-import { OneHotEncoder } from '../preprocessing/oneHotEncoder'
+import { OneHotEncoder } from '../preprocessing/OneHotEncoder'
 
 function getModelWeight(
   model: tf.Sequential
diff --git a/src/model_selection/crossValidator.ts b/src/model_selection/CrossValidator.ts
similarity index 100%
rename from src/model_selection/crossValidator.ts
rename to src/model_selection/CrossValidator.ts
diff --git a/src/model_selection/kFold.test.ts b/src/model_selection/KFold.test.ts
similarity index 99%
rename from src/model_selection/kFold.test.ts
rename to src/model_selection/KFold.test.ts
index 6f6a96c8..bb18ef14 100644
--- a/src/model_selection/kFold.test.ts
+++ b/src/model_selection/KFold.test.ts
@@ -14,7 +14,7 @@
 */
 
 import * as fc from 'fast-check'
-import { KFold } from './kFold'
+import { KFold } from './KFold'
 import { alea } from 'seedrandom'
 import '../jestTensorMatchers'
 import { tf } from '../shared/globals'
diff --git a/src/model_selection/kFold.ts b/src/model_selection/KFold.ts
similarity index 98%
rename from src/model_selection/kFold.ts
rename to src/model_selection/KFold.ts
index 7423feec..cf67abbb 100644
--- a/src/model_selection/kFold.ts
+++ b/src/model_selection/KFold.ts
@@ -14,7 +14,7 @@
 */
 
 import { assert } from '../typesUtils'
-import { CrossValidator } from './crossValidator'
+import { CrossValidator } from './CrossValidator'
 import * as randUtils from '../randUtils'
 import { Scikit1D, Scikit2D } from '../types'
 import { getLength } from '../utils'
@@ -81,7 +81,7 @@ export class KFold implements CrossValidator {
   nSplits: number
   shuffle: boolean
   randomState?: number
-
+  name: string
   constructor({
     nSplits = 5,
     shuffle = false,
@@ -95,6 +95,7 @@ export class KFold implements CrossValidator {
     this.nSplits = nSplits
     this.shuffle = Boolean(shuffle)
     this.randomState = randomState
+    this.name = 'KFold'
   }
 
   public getNumSplits(): number {
diff --git a/src/model_selection/crossValScore.ts b/src/model_selection/crossValScore.ts
index bc4c1498..7d0b551c 100644
--- a/src/model_selection/crossValScore.ts
+++ b/src/model_selection/crossValScore.ts
@@ -14,8 +14,8 @@
 */
 
 import { assert } from '../typesUtils'
-import { CrossValidator } from './crossValidator'
-import { KFold } from './kFold'
+import { CrossValidator } from './CrossValidator'
+import { KFold } from './KFold'
 import { Scikit1D, Scikit2D } from '../types'
 import { isScikit1D } from '../typesUtils'
 import { convertToTensor1D, convertToTensor2D } from '../utils'
diff --git a/src/naive_bayes/baseNaiveBayes.ts b/src/naive_bayes/BaseNaiveBayes.ts
similarity index 100%
rename from src/naive_bayes/baseNaiveBayes.ts
rename to src/naive_bayes/BaseNaiveBayes.ts
diff --git a/src/naive_bayes/gaussianNaiveBayes.test.ts b/src/naive_bayes/GaussianNB.test.ts
similarity index 98%
rename from src/naive_bayes/gaussianNaiveBayes.test.ts
rename to src/naive_bayes/GaussianNB.test.ts
index 1936e59d..627018e8 100644
--- a/src/naive_bayes/gaussianNaiveBayes.test.ts
+++ b/src/naive_bayes/GaussianNB.test.ts
@@ -12,7 +12,7 @@
 * limitations under the License.
 * ==========================================================================
 */
-import { GaussianNB } from './gaussianNaiveBayes'
+import { GaussianNB } from './GaussianNB'
 
 describe('GaussianNB', function () {
   it('without priors', async () => {
diff --git a/src/naive_bayes/gaussianNaiveBayes.ts b/src/naive_bayes/GaussianNB.ts
similarity index 95%
rename from src/naive_bayes/gaussianNaiveBayes.ts
rename to src/naive_bayes/GaussianNB.ts
index 421c3af7..6801b841 100644
--- a/src/naive_bayes/gaussianNaiveBayes.ts
+++ b/src/naive_bayes/GaussianNB.ts
@@ -13,7 +13,7 @@
 * ==========================================================================
 */
 import { tf } from '../shared/globals'
-import { BaseNaiveBayes } from './baseNaiveBayes'
+import { BaseNaiveBayes } from './BaseNaiveBayes'
 
 /**
  * Gaussian Naive Bayes classifier
@@ -45,6 +45,7 @@ import { BaseNaiveBayes } from './baseNaiveBayes'
  *
  */
 export class GaussianNB extends BaseNaiveBayes {
+  name = 'GaussianNB'
   protected kernel(
     features: tf.Tensor2D,
     mean: tf.Tensor1D,
diff --git a/src/neighbors/bruteNeighborhood.test.ts b/src/neighbors/BruteNeighborhood.test.ts
similarity index 93%
rename from src/neighbors/bruteNeighborhood.test.ts
rename to src/neighbors/BruteNeighborhood.test.ts
index 0bf4f787..b263ff51 100644
--- a/src/neighbors/bruteNeighborhood.test.ts
+++ b/src/neighbors/BruteNeighborhood.test.ts
@@ -14,7 +14,7 @@
 */
 
 import { neighborhoodGenericTests } from './neighborhoodGenericTests'
-import { BruteNeighborhood } from './bruteNeighborhood'
+import { BruteNeighborhood } from './BruteNeighborhood'
 
 neighborhoodGenericTests(
   'BruteNeighborhood',
diff --git a/src/neighbors/bruteNeighborhood.ts b/src/neighbors/BruteNeighborhood.ts
similarity index 95%
rename from src/neighbors/bruteNeighborhood.ts
rename to src/neighbors/BruteNeighborhood.ts
index c0a39655..720d7a1d 100644
--- a/src/neighbors/bruteNeighborhood.ts
+++ b/src/neighbors/BruteNeighborhood.ts
@@ -13,8 +13,8 @@
 * ==========================================================================
 */
 
-import { Neighborhood, NeighborhoodParams } from './neighborhood'
-import { Metric } from './metrics'
+import { Neighborhood, NeighborhoodParams } from './Neighborhood'
+import { Metric } from './Metric'
 import { tf } from '../shared/globals'
 import { assert } from '../typesUtils'
 
diff --git a/src/neighbors/cappedMaxHeap.test.ts b/src/neighbors/CappedMaxHeap.test.ts
similarity index 97%
rename from src/neighbors/cappedMaxHeap.test.ts
rename to src/neighbors/CappedMaxHeap.test.ts
index 64956345..181d8ea9 100644
--- a/src/neighbors/cappedMaxHeap.test.ts
+++ b/src/neighbors/CappedMaxHeap.test.ts
@@ -15,7 +15,7 @@
 
 import * as fc from 'fast-check'
 
-import { CappedMaxHeap } from './cappedMaxHeap'
+import { CappedMaxHeap } from './CappedMaxHeap'
 
 describe('CappedMaxHeap', () => {
   const anyFloat = () =>
diff --git a/src/neighbors/cappedMaxHeap.ts b/src/neighbors/CappedMaxHeap.ts
similarity index 100%
rename from src/neighbors/cappedMaxHeap.ts
rename to src/neighbors/CappedMaxHeap.ts
diff --git a/src/neighbors/kNeighborsBase.ts b/src/neighbors/KNeighborsBase.ts
similarity index 96%
rename from src/neighbors/kNeighborsBase.ts
rename to src/neighbors/KNeighborsBase.ts
index af80ed9a..3b4dd715 100644
--- a/src/neighbors/kNeighborsBase.ts
+++ b/src/neighbors/KNeighborsBase.ts
@@ -13,14 +13,14 @@
 * ==========================================================================
 */
 
-import { Neighborhood, NeighborhoodParams } from './neighborhood'
-import { BruteNeighborhood } from './bruteNeighborhood'
-import { minkowskiMetric } from './metrics'
+import { Neighborhood, NeighborhoodParams } from './Neighborhood'
+import { BruteNeighborhood } from './BruteNeighborhood'
+import { minkowskiMetric } from './Metric'
 import { Scikit1D, Scikit2D } from '../types'
 import { convertToNumericTensor1D, convertToNumericTensor2D } from '../utils'
 import { assert } from '../typesUtils'
 import { tf } from '../shared/globals'
-import { KdTree } from './kdTree'
+import { KdTree } from './KdTree'
 import Serialize from '../serialize'
 
 const WEIGHTS_FUNCTIONS = {
diff --git a/src/neighbors/kNeighborsClassifier.test.ts b/src/neighbors/KNeighborsClassifier.test.ts
similarity index 97%
rename from src/neighbors/kNeighborsClassifier.test.ts
rename to src/neighbors/KNeighborsClassifier.test.ts
index 0226bf88..559a72df 100644
--- a/src/neighbors/kNeighborsClassifier.test.ts
+++ b/src/neighbors/KNeighborsClassifier.test.ts
@@ -13,11 +13,11 @@
 * ==========================================================================
 */
 
-import { KNeighborsClassifier } from './kNeighborsClassifier'
-import { KNeighborsParams } from './kNeighborsBase'
+import { KNeighborsClassifier } from './KNeighborsClassifier'
+import { KNeighborsParams } from './KNeighborsBase'
 import { dataUrls } from '../datasets/datasets'
 import { crossValScore } from '../model_selection/crossValScore'
-import { KFold } from '../model_selection/kFold'
+import { KFold } from '../model_selection/KFold'
 import { arrayEqual } from '../utils'
 import '../jestTensorMatchers'
 import * as dfd from 'danfojs-node'
diff --git a/src/neighbors/kNeighborsClassifier.ts b/src/neighbors/KNeighborsClassifier.ts
similarity index 97%
rename from src/neighbors/kNeighborsClassifier.ts
rename to src/neighbors/KNeighborsClassifier.ts
index 534008ad..cc38d9a3 100644
--- a/src/neighbors/kNeighborsClassifier.ts
+++ b/src/neighbors/KNeighborsClassifier.ts
@@ -14,7 +14,7 @@
 */
 
 import { Scikit1D, Scikit2D } from '../types'
-import { KNeighborsBase } from './kNeighborsBase'
+import { KNeighborsBase } from './KNeighborsBase'
 import { convertToNumericTensor2D, convertToTensor1D } from '../utils'
 import { polyfillUnique } from '../tfUtils'
 import { accuracy } from '../model_selection/scorers'
@@ -44,6 +44,7 @@ export class KNeighborsClassifier extends KNeighborsBase {
 
   score = accuracy
 
+  name = 'KNeighborsClassifier'
   /**
    * Applies this mdodel to predict the class probabilities of each given sample.
    *
diff --git a/src/neighbors/kNeighborsRegressor.test.ts b/src/neighbors/KNeighborsRegressor.test.ts
similarity index 96%
rename from src/neighbors/kNeighborsRegressor.test.ts
rename to src/neighbors/KNeighborsRegressor.test.ts
index 58dd53fa..50c5c418 100644
--- a/src/neighbors/kNeighborsRegressor.test.ts
+++ b/src/neighbors/KNeighborsRegressor.test.ts
@@ -13,12 +13,12 @@
 * ==========================================================================
 */
 
-import { KNeighborsRegressor } from './kNeighborsRegressor'
-import { KNeighborsParams } from './kNeighborsBase'
+import { KNeighborsRegressor } from './KNeighborsRegressor'
+import { KNeighborsParams } from './KNeighborsBase'
 import { dataUrls } from '../datasets/datasets'
 import { arrayEqual } from '../utils'
 import { crossValScore } from '../model_selection/crossValScore'
-import { KFold } from '../model_selection/kFold'
+import { KFold } from '../model_selection/KFold'
 import { negMeanSquaredError } from '../model_selection/scorers'
 import '../jestTensorMatchers'
 import * as dfd from 'danfojs-node'
diff --git a/src/neighbors/kNeighborsRegressor.ts b/src/neighbors/KNeighborsRegressor.ts
similarity index 96%
rename from src/neighbors/kNeighborsRegressor.ts
rename to src/neighbors/KNeighborsRegressor.ts
index 0f955982..8bda66f7 100644
--- a/src/neighbors/kNeighborsRegressor.ts
+++ b/src/neighbors/KNeighborsRegressor.ts
@@ -14,7 +14,7 @@
 */
 
 import { Scikit2D } from '../types'
-import { KNeighborsBase } from '../neighbors/kNeighborsBase'
+import { KNeighborsBase } from './KNeighborsBase'
 import { convertToNumericTensor2D } from '../utils'
 import { tf } from '../shared/globals'
 
@@ -45,6 +45,7 @@ export class KNeighborsRegressor extends KNeighborsBase {
    * @param y The predicted targets `y` where `y[i]` is the prediction
    *          for sample `X[i,:]`
    */
+  name = 'KNeighborsRegressor'
   public predict(X: Scikit2D) {
     const { neighborhood, y, nNeighbors, weightsFn } = this._getFitParams()
 
diff --git a/src/neighbors/kdTree.test.ts b/src/neighbors/KdTree.test.ts
similarity index 95%
rename from src/neighbors/kdTree.test.ts
rename to src/neighbors/KdTree.test.ts
index 3f452ee7..87736ed3 100644
--- a/src/neighbors/kdTree.test.ts
+++ b/src/neighbors/KdTree.test.ts
@@ -14,6 +14,6 @@
 */
 
 import { neighborhoodGenericTests } from './neighborhoodGenericTests'
-import { KdTree } from './kdTree'
+import { KdTree } from './KdTree'
 
 neighborhoodGenericTests('KdTree', KdTree.build)
diff --git a/src/neighbors/kdTree.ts b/src/neighbors/KdTree.ts
similarity index 98%
rename from src/neighbors/kdTree.ts
rename to src/neighbors/KdTree.ts
index 3a4e15e6..9a8750d5 100644
--- a/src/neighbors/kdTree.ts
+++ b/src/neighbors/KdTree.ts
@@ -15,10 +15,10 @@
 
 import { assert } from '../typesUtils'
 import { tf } from '../shared/globals'
-import { Neighborhood, NeighborhoodParams } from './neighborhood'
+import { Neighborhood, NeighborhoodParams } from './Neighborhood'
 import * as randUtils from '../randUtils'
 import { alea } from 'seedrandom'
-import { CappedMaxHeap } from './cappedMaxHeap'
+import { CappedMaxHeap } from './CappedMaxHeap'
 
 const child = (parent: number) => (parent << 1) + 1
 const parent = (child: number) => (child - 1) >> 1
diff --git a/src/neighbors/metrics.test.ts b/src/neighbors/Metric.test.ts
similarity index 99%
rename from src/neighbors/metrics.test.ts
rename to src/neighbors/Metric.test.ts
index a754028f..c05c5125 100644
--- a/src/neighbors/metrics.test.ts
+++ b/src/neighbors/Metric.test.ts
@@ -15,7 +15,7 @@
 
 import * as fc from 'fast-check'
 
-import { Metric, minkowskiMetric } from './metrics'
+import { Metric, minkowskiMetric } from './Metric'
 
 const NDIMS = Object.freeze([1, 2, 7])
 
diff --git a/src/neighbors/metrics.ts b/src/neighbors/Metric.ts
similarity index 100%
rename from src/neighbors/metrics.ts
rename to src/neighbors/Metric.ts
diff --git a/src/neighbors/neighborhood.ts b/src/neighbors/Neighborhood.ts
similarity index 98%
rename from src/neighbors/neighborhood.ts
rename to src/neighbors/Neighborhood.ts
index 6c98dca3..266822f2 100644
--- a/src/neighbors/neighborhood.ts
+++ b/src/neighbors/Neighborhood.ts
@@ -14,7 +14,7 @@
 */
 
 import { tf } from '../shared/globals'
-import { Metric } from './metrics'
+import { Metric } from './Metric'
 
 /**
  * Default constructor parameters for {@link Neighborhood} instances.
diff --git a/src/neighbors/neighborhoodGenericTests.ts b/src/neighbors/neighborhoodGenericTests.ts
index b3e9f6c0..ce335682 100644
--- a/src/neighbors/neighborhoodGenericTests.ts
+++ b/src/neighbors/neighborhoodGenericTests.ts
@@ -16,9 +16,9 @@
 import * as fc from 'fast-check'
 import { tf } from '../shared/globals'
 import { alea } from 'seedrandom'
-import { Neighborhood, NeighborhoodParams } from './neighborhood'
+import { Neighborhood, NeighborhoodParams } from './Neighborhood'
 import { lhs, shuffle } from '../randUtils'
-import { minkowskiMetric } from './metrics'
+import { minkowskiMetric } from './Metric'
 import { polyfillUnique } from '../tfUtils'
 import '../jestTensorMatchers'
 
diff --git a/src/pipeline/pipeline.test.ts b/src/pipeline/Pipeline.test.ts
similarity index 93%
rename from src/pipeline/pipeline.test.ts
rename to src/pipeline/Pipeline.test.ts
index 5097b750..52ead335 100644
--- a/src/pipeline/pipeline.test.ts
+++ b/src/pipeline/Pipeline.test.ts
@@ -1,9 +1,9 @@
-import { Pipeline, makePipeline } from './pipeline'
+import { Pipeline, makePipeline } from './Pipeline'
 import { tf } from '../shared/globals'
 import { tensorEqual } from '../utils'
-import { LinearRegression } from '../linear_model/linearRegression'
-import { SimpleImputer } from '../impute/simpleImputer'
-import { MinMaxScaler } from '../preprocessing/minMaxScaler'
+import { LinearRegression } from '../linear_model/LinearRegression'
+import { SimpleImputer } from '../impute/SimpleImputer'
+import { MinMaxScaler } from '../preprocessing/MinMaxScaler'
 
 describe('Pipeline', function () {
   it('Use a Pipeline (min-max scaler, and linear regression)', async function () {
diff --git a/src/pipeline/pipeline.ts b/src/pipeline/Pipeline.ts
similarity index 99%
rename from src/pipeline/pipeline.ts
rename to src/pipeline/Pipeline.ts
index 8344949d..6cf5e6c4 100644
--- a/src/pipeline/pipeline.ts
+++ b/src/pipeline/Pipeline.ts
@@ -48,7 +48,7 @@ export class Pipeline extends Serialize {
   steps: Array<[string, any]>
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'pipeline'
+  name = 'Pipeline'
 
   constructor({ steps = [] }: PipelineParams = {}) {
     super()
diff --git a/src/preprocessing/labelEncoder.test.ts b/src/preprocessing/LabelEncoder.test.ts
similarity index 96%
rename from src/preprocessing/labelEncoder.test.ts
rename to src/preprocessing/LabelEncoder.test.ts
index 0f3d8945..062929c8 100644
--- a/src/preprocessing/labelEncoder.test.ts
+++ b/src/preprocessing/LabelEncoder.test.ts
@@ -1,4 +1,4 @@
-import { LabelEncoder } from './labelEncoder'
+import { LabelEncoder } from './LabelEncoder'
 import * as dfd from 'danfojs-node'
 
 describe('LabelEncoder', function () {
diff --git a/src/preprocessing/labelEncoder.ts b/src/preprocessing/LabelEncoder.ts
similarity index 99%
rename from src/preprocessing/labelEncoder.ts
rename to src/preprocessing/LabelEncoder.ts
index 94278599..9067e707 100644
--- a/src/preprocessing/labelEncoder.ts
+++ b/src/preprocessing/LabelEncoder.ts
@@ -41,7 +41,7 @@ export class LabelEncoder extends Serialize {
   classes: Array<string | number | boolean>
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'labelencoder'
+  name = 'LabelEncoder'
 
   constructor() {
     super()
diff --git a/src/preprocessing/maxAbsScaler.test.ts b/src/preprocessing/MaxAbsScaler.test.ts
similarity index 99%
rename from src/preprocessing/maxAbsScaler.test.ts
rename to src/preprocessing/MaxAbsScaler.test.ts
index c653d115..b69f584a 100644
--- a/src/preprocessing/maxAbsScaler.test.ts
+++ b/src/preprocessing/MaxAbsScaler.test.ts
@@ -1,4 +1,4 @@
-import { MaxAbsScaler } from './maxAbsScaler'
+import { MaxAbsScaler } from './MaxAbsScaler'
 import * as dfd from 'danfojs-node'
 import { tf } from '../shared/globals'
 import { arrayEqual } from '../utils'
diff --git a/src/preprocessing/maxAbsScaler.ts b/src/preprocessing/MaxAbsScaler.ts
similarity index 99%
rename from src/preprocessing/maxAbsScaler.ts
rename to src/preprocessing/MaxAbsScaler.ts
index f2acccde..a0c7a818 100644
--- a/src/preprocessing/maxAbsScaler.ts
+++ b/src/preprocessing/MaxAbsScaler.ts
@@ -67,7 +67,7 @@ export class MaxAbsScaler extends TransformerMixin {
   featureNamesIn: Array<string>
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'maxabsscaler'
+  name = 'MaxAbsScaler'
 
   constructor() {
     super()
diff --git a/src/preprocessing/minMaxScaler.test.ts b/src/preprocessing/MinMaxScaler.test.ts
similarity index 99%
rename from src/preprocessing/minMaxScaler.test.ts
rename to src/preprocessing/MinMaxScaler.test.ts
index cb4def7e..7b15cc47 100644
--- a/src/preprocessing/minMaxScaler.test.ts
+++ b/src/preprocessing/MinMaxScaler.test.ts
@@ -1,4 +1,4 @@
-import { MinMaxScaler } from './minMaxScaler'
+import { MinMaxScaler } from './MinMaxScaler'
 import * as dfd from 'danfojs-node'
 import { isDataFrameInterface, isSeriesInterface } from '../typesUtils'
 import { ScikitVecOrMatrix } from '../types'
diff --git a/src/preprocessing/minMaxScaler.ts b/src/preprocessing/MinMaxScaler.ts
similarity index 99%
rename from src/preprocessing/minMaxScaler.ts
rename to src/preprocessing/MinMaxScaler.ts
index a35a5ebb..fe37e04d 100644
--- a/src/preprocessing/minMaxScaler.ts
+++ b/src/preprocessing/MinMaxScaler.ts
@@ -83,7 +83,7 @@ export class MinMaxScaler extends TransformerMixin implements Transformer {
   featureNamesIn: Array<string>
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'minmaxscaler'
+  name = 'MinMaxScaler'
 
   constructor({ featureRange = [0, 1] }: MinMaxScalerParams = {}) {
     super()
diff --git a/src/preprocessing/normalizer.test.ts b/src/preprocessing/Normalizer.test.ts
similarity index 97%
rename from src/preprocessing/normalizer.test.ts
rename to src/preprocessing/Normalizer.test.ts
index e9672987..65d20877 100644
--- a/src/preprocessing/normalizer.test.ts
+++ b/src/preprocessing/Normalizer.test.ts
@@ -1,4 +1,4 @@
-import { Normalizer } from './normalizer'
+import { Normalizer } from './Normalizer'
 import * as dfd from 'danfojs-node'
 import { arrayEqual } from '../utils'
 
diff --git a/src/preprocessing/normalizer.ts b/src/preprocessing/Normalizer.ts
similarity index 99%
rename from src/preprocessing/normalizer.ts
rename to src/preprocessing/Normalizer.ts
index 954fd678..e02cc70a 100644
--- a/src/preprocessing/normalizer.ts
+++ b/src/preprocessing/Normalizer.ts
@@ -65,7 +65,7 @@ export class Normalizer extends TransformerMixin {
   featureNamesIn: Array<string>
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'normalizer'
+  name = 'Normalizer'
 
   constructor({ norm = 'l2' }: NormalizerParams = {}) {
     super()
diff --git a/src/preprocessing/oneHotEncoder.test.ts b/src/preprocessing/OneHotEncoder.test.ts
similarity index 98%
rename from src/preprocessing/oneHotEncoder.test.ts
rename to src/preprocessing/OneHotEncoder.test.ts
index fe3511e8..35100413 100644
--- a/src/preprocessing/oneHotEncoder.test.ts
+++ b/src/preprocessing/OneHotEncoder.test.ts
@@ -1,5 +1,5 @@
 import { tf } from '../shared/globals'
-import { OneHotEncoder } from './oneHotEncoder'
+import { OneHotEncoder } from './OneHotEncoder'
 import { arrayTo2DColumn } from '../utils'
 
 describe('OneHotEncoder', function () {
diff --git a/src/preprocessing/oneHotEncoder.ts b/src/preprocessing/OneHotEncoder.ts
similarity index 99%
rename from src/preprocessing/oneHotEncoder.ts
rename to src/preprocessing/OneHotEncoder.ts
index 7c5f09d7..ea5f4f93 100644
--- a/src/preprocessing/oneHotEncoder.ts
+++ b/src/preprocessing/OneHotEncoder.ts
@@ -98,7 +98,7 @@ export class OneHotEncoder extends TransformerMixin {
   featureNamesIn: Array<string>
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'onehotencoder'
+  name = 'OneHotEncoder'
 
   constructor({
     categories = 'auto',
diff --git a/src/preprocessing/ordinalEncoder.test.ts b/src/preprocessing/OrdinalEncoder.test.ts
similarity index 97%
rename from src/preprocessing/ordinalEncoder.test.ts
rename to src/preprocessing/OrdinalEncoder.test.ts
index e28ee00f..57666262 100644
--- a/src/preprocessing/ordinalEncoder.test.ts
+++ b/src/preprocessing/OrdinalEncoder.test.ts
@@ -1,4 +1,4 @@
-import { OrdinalEncoder } from './ordinalEncoder'
+import { OrdinalEncoder } from './OrdinalEncoder'
 import { arrayTo2DColumn } from '../utils'
 
 describe('OrdinalEncoder', function () {
diff --git a/src/preprocessing/ordinalEncoder.ts b/src/preprocessing/OrdinalEncoder.ts
similarity index 99%
rename from src/preprocessing/ordinalEncoder.ts
rename to src/preprocessing/OrdinalEncoder.ts
index e03403c9..4eb78752 100644
--- a/src/preprocessing/ordinalEncoder.ts
+++ b/src/preprocessing/OrdinalEncoder.ts
@@ -89,7 +89,7 @@ export class OrdinalEncoder extends TransformerMixin {
   featureNamesIn: Array<string>
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'ordinalencoder'
+  name = 'OrdinalEncoder'
 
   constructor({
     categories = 'auto',
diff --git a/src/preprocessing/robustScaler.test.ts b/src/preprocessing/RobustScaler.test.ts
similarity index 97%
rename from src/preprocessing/robustScaler.test.ts
rename to src/preprocessing/RobustScaler.test.ts
index 2a25da53..3a31475e 100644
--- a/src/preprocessing/robustScaler.test.ts
+++ b/src/preprocessing/RobustScaler.test.ts
@@ -1,4 +1,4 @@
-import { RobustScaler } from './robustScaler'
+import { RobustScaler } from './RobustScaler'
 import * as dfd from 'danfojs-node'
 import { arrayEqual } from '../utils'
 
diff --git a/src/preprocessing/robustScaler.ts b/src/preprocessing/RobustScaler.ts
similarity index 99%
rename from src/preprocessing/robustScaler.ts
rename to src/preprocessing/RobustScaler.ts
index 4964a488..9a78f129 100644
--- a/src/preprocessing/robustScaler.ts
+++ b/src/preprocessing/RobustScaler.ts
@@ -107,7 +107,7 @@ export class RobustScaler extends TransformerMixin {
   withCentering: boolean
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'robustscaler'
+  name = 'RobustScaler'
 
   constructor({
     quantileRange = [25.0, 75.0],
diff --git a/src/preprocessing/standardScaler.test.ts b/src/preprocessing/StandardScaler.test.ts
similarity index 98%
rename from src/preprocessing/standardScaler.test.ts
rename to src/preprocessing/StandardScaler.test.ts
index a66c6ff1..e3830ef7 100644
--- a/src/preprocessing/standardScaler.test.ts
+++ b/src/preprocessing/StandardScaler.test.ts
@@ -1,4 +1,4 @@
-import { StandardScaler } from './standardScaler'
+import { StandardScaler } from './StandardScaler'
 import * as dfd from 'danfojs-node'
 
 describe('StandardScaler', function () {
diff --git a/src/preprocessing/standardScaler.ts b/src/preprocessing/StandardScaler.ts
similarity index 99%
rename from src/preprocessing/standardScaler.ts
rename to src/preprocessing/StandardScaler.ts
index c763dab7..90cd9dde 100644
--- a/src/preprocessing/standardScaler.ts
+++ b/src/preprocessing/StandardScaler.ts
@@ -86,7 +86,7 @@ export class StandardScaler extends TransformerMixin {
   featureNamesIn: Array<string>
 
   /** Useful for pipelines and column transformers to have a default name for transforms */
-  name = 'standardscaler'
+  name = 'StandardScaler'
 
   constructor({ withMean = true, withStd = true }: StandardScalerParams = {}) {
     super()
diff --git a/src/svm/linearSVC.test.ts b/src/svm/LinearSVC.test.ts
similarity index 97%
rename from src/svm/linearSVC.test.ts
rename to src/svm/LinearSVC.test.ts
index 7e41f37f..142a7034 100644
--- a/src/svm/linearSVC.test.ts
+++ b/src/svm/LinearSVC.test.ts
@@ -1,4 +1,4 @@
-import { LinearSVC } from './linearSVC'
+import { LinearSVC } from './LinearSVC'
 
 describe('LinearSVC', function () {
   it('Works on arrays (small example)', async function () {
diff --git a/src/svm/linearSVC.ts b/src/svm/LinearSVC.ts
similarity index 97%
rename from src/svm/linearSVC.ts
rename to src/svm/LinearSVC.ts
index 7f64be5c..bedd3c64 100644
--- a/src/svm/linearSVC.ts
+++ b/src/svm/LinearSVC.ts
@@ -13,7 +13,7 @@
 // * ==========================================================================
 // */
 
-import { SGDClassifier } from '../linear_model/sgdClassifier'
+import { SGDClassifier } from '../linear_model/SgdClassifier'
 import { tf } from '../shared/globals'
 
 // First pass at a LinearSVC implementation using gradient descent
diff --git a/src/svm/linearSVR.test.ts b/src/svm/LinearSVR.test.ts
similarity index 90%
rename from src/svm/linearSVR.test.ts
rename to src/svm/LinearSVR.test.ts
index b0d25001..2e325983 100644
--- a/src/svm/linearSVR.test.ts
+++ b/src/svm/LinearSVR.test.ts
@@ -1,4 +1,4 @@
-import { LinearSVR } from './linearSVR'
+import { LinearSVR } from './LinearSVR'
 
 import { tensorEqual } from '../utils'
 import { tf } from '../shared/globals'
diff --git a/src/svm/linearSVR.ts b/src/svm/LinearSVR.ts
similarity index 97%
rename from src/svm/linearSVR.ts
rename to src/svm/LinearSVR.ts
index f3daf8b1..f7efe1e0 100644
--- a/src/svm/linearSVR.ts
+++ b/src/svm/LinearSVR.ts
@@ -13,7 +13,7 @@
 // * ==========================================================================
 // */
 
-import { SGDRegressor } from '../linear_model/sgdRegressor'
+import { SGDRegressor } from '../linear_model/SgdRegressor'
 import { tf } from '../shared/globals'
 
 // First pass at a LinearSVC implementation using gradient descent
diff --git a/src/tree/criterion.test.ts b/src/tree/Criterion.test.ts
similarity index 99%
rename from src/tree/criterion.test.ts
rename to src/tree/Criterion.test.ts
index 551e18ed..c58617fc 100644
--- a/src/tree/criterion.test.ts
+++ b/src/tree/Criterion.test.ts
@@ -1,4 +1,4 @@
-import { ClassificationCriterion, giniCoefficient, entropy } from './criterion'
+import { ClassificationCriterion, giniCoefficient, entropy } from './Criterion'
 
 describe('Criterion', function () {
   let X = [
diff --git a/src/tree/criterion.ts b/src/tree/Criterion.ts
similarity index 100%
rename from src/tree/criterion.ts
rename to src/tree/Criterion.ts
diff --git a/src/tree/decisiontree.test.ts b/src/tree/DecisionTree.test.ts
similarity index 99%
rename from src/tree/decisiontree.test.ts
rename to src/tree/DecisionTree.test.ts
index cb500392..7e1a5207 100644
--- a/src/tree/decisiontree.test.ts
+++ b/src/tree/DecisionTree.test.ts
@@ -1,4 +1,4 @@
-import { DecisionTreeClassifier, DecisionTreeRegressor } from './decisiontree'
+import { DecisionTreeClassifier, DecisionTreeRegressor } from './DecisionTree'
 import { dataUrls } from '../datasets/datasets'
 import * as dfd from 'danfojs-node'
 
diff --git a/src/tree/decisiontree.ts b/src/tree/DecisionTree.ts
similarity index 98%
rename from src/tree/decisiontree.ts
rename to src/tree/DecisionTree.ts
index ca5c67f7..292dca08 100644
--- a/src/tree/decisiontree.ts
+++ b/src/tree/DecisionTree.ts
@@ -1,13 +1,13 @@
-import { ImpurityMeasure } from './criterion'
-import { Splitter } from './splitter'
+import { ImpurityMeasure } from './Criterion'
+import { Splitter } from './Splitter'
 import { int } from '../randUtils'
 import { r2Score, accuracyScore } from '../metrics/metrics'
-import { Split, makeDefaultSplit } from './splitter'
+import { Split, makeDefaultSplit } from './Splitter'
 import { assert, isScikit1D, isScikit2D } from '../typesUtils'
 import { validateX, validateY } from './utils'
 import { Scikit1D, Scikit2D } from '../types'
 import { convertScikit2DToArray, convertScikit1DToArray } from '../utils'
-import { LabelEncoder } from '../preprocessing/labelEncoder'
+import { LabelEncoder } from '../preprocessing/LabelEncoder'
 import Serialize from '../serialize'
 
 /*
@@ -396,7 +396,7 @@ export class DecisionTreeClassifier extends DecisionTreeBase {
       minImpurityDecrease
     })
     this.labelEncoder = new LabelEncoder()
-    this.name = 'decisionTreeClassifier'
+    this.name = 'DecisionTreeClassifier'
   }
   public fit(X: Scikit2D, y: Scikit1D): DecisionTreeClassifier {
     assert(isScikit1D(y), 'y value is not a 1D container')
@@ -489,7 +489,7 @@ export class DecisionTreeRegressor extends DecisionTreeBase {
       maxFeatures,
       minImpurityDecrease
     })
-    this.name = 'decisionTreeRegressor'
+    this.name = 'DecisionTreeRegressor'
   }
   public fit(X: Scikit2D, y: Scikit1D): DecisionTreeRegressor {
     assert(isScikit1D(y), 'y value is not a 1D container')
diff --git a/src/tree/splitter.test.ts b/src/tree/Splitter.test.ts
similarity index 98%
rename from src/tree/splitter.test.ts
rename to src/tree/Splitter.test.ts
index feac7fe8..ff7d7a6c 100644
--- a/src/tree/splitter.test.ts
+++ b/src/tree/Splitter.test.ts
@@ -1,5 +1,5 @@
-import { ImpurityMeasure } from './criterion'
-import { Splitter } from './splitter'
+import { ImpurityMeasure } from './Criterion'
+import { Splitter } from './Splitter'
 
 describe('Splitter', function () {
   let types = ['gini', 'entropy', 'squared_error']
diff --git a/src/tree/splitter.ts b/src/tree/Splitter.ts
similarity index 99%
rename from src/tree/splitter.ts
rename to src/tree/Splitter.ts
index 93c331b3..e7fbbb60 100644
--- a/src/tree/splitter.ts
+++ b/src/tree/Splitter.ts
@@ -2,7 +2,7 @@ import {
   ClassificationCriterion,
   RegressionCriterion,
   ImpurityMeasure
-} from './criterion'
+} from './Criterion'
 import { shuffle } from 'lodash'
 import { int } from '../randUtils'
 import Serialize from '../serialize'

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