Most popular metrics used to evaluate object detection algorithms.

Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.

BEST SCORE ON KAGGLE SO FAR , EVEN BETTER THAN THE KAGGLE TEAM MEMBER WHO DID BEST SO FAR. The project is about diagnosing pneumonia from XRay images of lungs of a person using self laid convolutional neural network and tranfer learning via inceptionV3. The images were of size greater than 1000 pixels per dimension and the total dataset was tagg…

Unofficial Python implementation of "Precision and Recall for Time Series".

Evaluation of 3D detection and diagnosis performance —geared towards prostate cancer detection in MRI.

Time-series Aware Precision and Recall for Evaluating Anomaly Detection Methods

Machine learning utility functions and classes.

Report various statistics stemming from a confusion matrix in a tidy fashion. 🎯

ML/CNN Evaluation Metrics Package

LSTM based model for Named Entity Recognition Task using pytorch and GloVe embeddings

The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidate…

An information retrieval system which consists of various techniques' implementations like indexing, tokenization, stopping, stemming, page ranking, snippet generation and evaluation of results

BGU, Information Retrieval final project. Search-engine, Wikipedia corpus.

📊Course 3: Machine Learning Specialization course of Coursera by the University of Washington on Classification

Developed a Convolutional Neural Network based on VGG16 architecture to diagnose COVID-19 and classify chest X-rays of patients suffering from COVID-19, Ground Glass Opacity and Viral Pneumonia. This repository contains the link to the dataset, python code for visualizing the obtained data and developing the model using Keras API.

This is the official implementation for the Generative Modeling Density Alignment (GMDA). This work was presented in the paper "Frugal Generative Modeling for Tabular Data" at ECML 2024.

Classification problem using multiple ML Algorithms

Classification Metric Manager is metrics calculator for machine learning classification quality such as Precision, Recall, F-score, etc.

Resample precision-recall curves correctly!

Built a fraud detection system to handle an imbalanced credit card transaction dataset using SMOTE and NearMiss for data balancing. Trained multiple models, including Logistic Regression, SVM, Random Forest, and a Neural Network, to detect fraud accurately. Evaluated performance using Precision-Recall AUC, F1-score, and ROC-AUC