rafaelpadilla/Object-Detection-Metrics

Most popular metrics used to evaluate object detection algorithms.

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rafaelpadilla/review_object_detection_metrics

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.

Language: Python - Size: 37.2 MB - Last synced at: 17 days ago - Pushed at: over 1 year ago - Stars: 1,102 - Forks: 219

KasiMuthuveerappan/LoanTap-LogisticRegression

📔 This repository delves into Logistic Regression for loan approval prediction at LoanTap. It covers data preprocessing, model development, evaluation metrics, and strategic business recommendations. Explore model optimization techniques such as confusion matrix, precision, recall, Roc curve and F1 score to effectively mitigate default risks.

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Salma0-8/Credit-Card-Fraud-Detection-A-Comprehensive-Machine-Learning-Approach

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

Language: Jupyter Notebook - Size: 251 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0

DIAGNijmegen/picai_eval

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

Language: Python - Size: 810 KB - Last synced at: about 7 hours ago - Pushed at: 3 months ago - Stars: 22 - Forks: 11

VivekSagarSingh/Probability-of-Credit-card-Default

Classification problem using multiple ML Algorithms

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MohamedLotfy989/Credit-Card-Fraud-Detection

This repository focuses on credit card fraud detection using machine learning models, addressing class imbalance with SMOTE & undersampling, and optimizing performance via Grid Search & RandomizedSearchCV. It explores Logistic Regression, Random Forest, Voting Classifier, and XGBoost. balancing precision-recall trade-offs for fraud detection.

Language: Jupyter Notebook - Size: 3.39 MB - Last synced at: 25 days ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

hymn-ing/text-retrieval-by-posting-list

Language: C++ - Size: 43.3 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

LegallyNotBlonde/credit-risk-classification

Built a Logistic Regression model to predict loan risk, focusing on credit risk management with precision, recall, and F1-score evaluation

Language: Jupyter Notebook - Size: 610 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

Shlok-Nahar/mnist-cnn-classifier

This repository trains and evaluates three CNN models on MNIST, providing performance comparisons and 5 unique visualizations.

Language: Python - Size: 36.6 MB - Last synced at: 25 days ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

Zen204/-my-ecornell-portfolio

Includes all of my Jupyter Notebook assignments from my time at MIT's Break Through AI/ML Program.

Language: Jupyter Notebook - Size: 9.24 MB - Last synced at: 29 days ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

akbaritabar/gender-classification-precision-recall-f1-score

Calculating precision recall f1-score for gender classification methods

Language: HTML - Size: 443 KB - Last synced at: 23 days ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

alaazamelDev/text-based-search-engine

Implementation of a search engine using TF-IDF and Word Embedding-based vectorization techniques for efficient document retrieval

Language: Jupyter Notebook - Size: 1.15 MB - Last synced at: 18 days ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

manjugovindarajan/EasyVisa-US-visa-applicant-profiling-using-ML

Analyze data of US work Visa applicants, build a predictive model to facilitate approvals, and based on factors that significantly influence visa status, recommend profiles for whom visa should be certified or denied.

Language: Jupyter Notebook - Size: 1.55 MB - Last synced at: 7 months ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

IgorAugust0/information-retrieval

ℹ️ Information Retrieval models implemented in Python

Language: Python - Size: 8.74 MB - Last synced at: about 1 month ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

Niteshchawla/OLA-EnsembleLearning

Recruiting and retaining drivers is seen by industry watchers as a tough battle for Ola. Churn among drivers is high and it’s very easy for drivers to stop working for the service on the fly or jump to Uber depending on the rates.

Language: Jupyter Notebook - Size: 1.25 MB - Last synced at: about 2 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

Niteshchawla/LoanTap-LogisticRegression

Given a set of attributes for an Individual, determine if a credit line should be extended to them. If so, what should the repayment terms be in business recommendations?

Language: Jupyter Notebook - Size: 2.29 MB - Last synced at: about 2 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

ablacan/gmda

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.

Language: Python - Size: 505 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

Gauravhulmukh/Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras

Language: Jupyter Notebook - Size: 350 KB - Last synced at: 10 months ago - Pushed at: almost 6 years ago - Stars: 1 - Forks: 0

riccardoprosdocimi/ml-predictive-maintenance

This repository contains code and documentation for a machine learning project focused on predictive maintenance in industrial machinery. The project explores the development of a comprehensive predictive maintenance system using various machine learning techniques.

Language: Jupyter Notebook - Size: 3.7 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 1

avid7-tech/Predicting-stars-galaxies-and-quasars-using-ML-algorithms

This repository contains code for classifying galaxies into three classes: Galaxy, Quasar, and Star, using machine learning techniques. The dataset used in this project is the Sloan Digital Sky Survey (SDSS) dataset.

Language: Jupyter Notebook - Size: 5.82 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

Aalaa4444/Garbage_Classification

CNN model to classify garbage

Language: Jupyter Notebook - Size: 454 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

chakshuahuja/CS839

Submissions for Data Science: Principles, Algorithms, and Applications (CS839) @ UW-Madison

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neeraj1397/Radiography-Based-Diagnosis-Of-COVID-19-Using-Deep-Learning

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.

Language: Jupyter Notebook - Size: 1.22 MB - Last synced at: about 1 year ago - Pushed at: about 4 years ago - Stars: 3 - Forks: 0

lucas-penalva/classifier-learn-to-rank

(projeto ainda não finalizado) - Este repositório contém um projeto de uma seguradora deseja começar a vender seguro de veículos para clientes que já possuem plano de saúde.

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sajidahmed12/YOLOv5-precision-recall-f1-score

Language: Python - Size: 7.81 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

CompML/PRTS

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

Language: Python - Size: 197 KB - Last synced at: 9 months ago - Pushed at: about 4 years ago - Stars: 38 - Forks: 3

Ashwin0229/Collaborative-Filtering-K-nearest-neighbors-and-SVM

Using Collaborative Filtering predicting Movie Rating and K-nearest Neighbours & SVM algorithms for Number ClassificationNumber Classification

Language: Python - Size: 95.7 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

kamatameya9/Information-Retrieval-Assignment-2

Built a simple search system using Lucene. Indexed 100 text documents using the bbc-news sports dataset. Showed the impact of indexing the data well on precision and recall. Have included the queries used to arrive at the precision and recall.

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WINKAM/Classification-Metrics-Manager

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

Language: Python - Size: 8.79 KB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 3 - Forks: 1

chandru-engineer/MNIST-Classification-

In this project, the numeric digits are classified by using deep learning algorithm.

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m-clark/confusionMatrix

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

Language: R - Size: 432 KB - Last synced at: 26 days ago - Pushed at: almost 5 years ago - Stars: 11 - Forks: 4

deadskull7/Pneumonia-Diagnosis-using-XRays-96-percent-Recall

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 tagged large and had a space of 1GB+ . My work includes self laid neural network which was repeatedly tuned for one of the best hyperparameters and used variety of utility function of keras like callbacks for learning rate and checkpointing. Could have augmented the image data for even better modelling but was short of RAM on kaggle kernel. Other metrics like precision , recall and f1 score using confusion matrix were taken off special care. The other part included a brief introduction of transfer learning via InceptionV3 and was tuned entirely rather than partially after loading the inceptionv3 weights for the maximum achieved accuracy on kaggle till date. This achieved even a higher precision than before.

Language: Jupyter Notebook - Size: 1.48 MB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 97 - Forks: 77

Xu-Justin/detection-benchmark

Evaluate a detection model performance

Language: Python - Size: 506 KB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

Ola76/HR_analytics

Human Resources Analytics

Language: Jupyter Notebook - Size: 1.89 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

Ola76/SUV_data

In the project, SUV data was obtained from Kaggle.com. The aim is to understand which customers can purchase a new car.

Language: Jupyter Notebook - Size: 789 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

ash-0521/Abandoned-Object-Detection-in-crowded-environment-using-MATLAB

Trained MATLAB models for 82% precision/80% recall, optimized with blob analysis for 25% performance boost. User-friendly alarm system with 500+ engaged users.

Size: 682 KB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

mandyiv/Easy-Visa-Project

The objective of this analysis is to find patterns within the dataset to gain further understanding of the data and leverage it to choose a machine learning algorithm that can recommend a suitable profile for the applicants whose visa should be certified or denied

Language: Jupyter Notebook - Size: 1.99 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

SaadTariq01DataAnalyst/Prediction-of-Bank-Churn-Customer

The goal of this project is to develop a machine learning model that can help banks to identify customers who are likely to churn and take appropriate measures to retain them

Language: Jupyter Notebook - Size: 309 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

stefmolin/ml-utils

Machine learning utility functions and classes.

Language: Python - Size: 230 KB - Last synced at: about 9 hours ago - Pushed at: over 2 years ago - Stars: 12 - Forks: 14

JitalEn/LeadScore

Lead scoring case study

Language: Jupyter Notebook - Size: 1.33 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

zakarich/TF-IDF-cranDataSet

Language: Jupyter Notebook - Size: 695 KB - Last synced at: almost 2 years ago - Pushed at: about 5 years ago - Stars: 2 - Forks: 0

danort92/Anti-Spam-Software-for-University-Mail

Mail SPAM Detector

Language: Jupyter Notebook - Size: 190 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

danort92/Prediction-of-Cross-sell-Opportunities-for-Insurance-Policies

Insurance Cross Sell Opportunity Forecast through machine learning algorithm

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Mr-TalhaIlyas/Evaluation-Metrics-Package-Tensorflow-PyTorch-Keras

ML/CNN Evaluation Metrics Package

Size: 2.45 MB - Last synced at: 19 days ago - Pushed at: over 2 years ago - Stars: 9 - Forks: 2

Adarsh-sophos/Smart-Library

Identifying Books on Library Shelves using Supervised Deep Learning.

Language: Jupyter Notebook - Size: 469 MB - Last synced at: about 2 years ago - Pushed at: almost 6 years ago - Stars: 0 - Forks: 1

grvnair/heart-failure-prediction

Compared the metrics and performance of different classification algorithms on Heart Failure dataset from UCI ML Repository

Language: Jupyter Notebook - Size: 292 KB - Last synced at: almost 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

rochitasundar/Customer-profiling-using-ML-EasyVisa

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 candidates more likely to have the visa certified.

Language: Jupyter Notebook - Size: 7.68 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 6 - Forks: 2

parshva45/Information-Retrieval-System

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

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OmerHanan1/IR-final-project

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

Language: Jupyter Notebook - Size: 331 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0

cbrito3/Credit_Risk_Analysis

Supervised Machine Learning and Credit Risk

Language: Jupyter Notebook - Size: 986 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

saima8/Low-Birth-Weight-Prediction

Early Prediction of Birth weight Based on Maternal Factors using Machine Learning.

Language: Jupyter Notebook - Size: 4.65 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 1

laclouis5/Yolo-Box-Parser 📦

A Swift implementation of mAP computation for Yolo-style detections

Language: Swift - Size: 73.2 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0

saurf4ng/TaPR

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

Language: Python - Size: 24.4 KB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 17 - Forks: 6

baaraban/pytorch_ner

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

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emaynard10/Credit_Risk_Analysis

Using supervised machine learning to predict credit risk. Trying oversampling, under sampling, combination sampling and ensemble learning to find the model with the best fit

Language: Jupyter Notebook - Size: 20.7 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

rochitasundar/Classification-booking-cancelation-prediction-StarHotels

The aim is to develop an ML- based predictive classification model (logistic regression & decision trees) to predict which hotel booking is likely to be canceled. This is done by analysing different attributes of customer's booking details. Being able to predict accurately in advance if a booking is likely to be canceled will help formulate profitable policies for cancelations & refunds.

Language: Jupyter Notebook - Size: 7 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 1

mayankchaudhary26/Classification

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

Size: 101 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 1

neoyung/credit-card-fraud-detection

Fraud detection with SMOTE (Synthetic Minority Over-sampling Technique)

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ameya98/pr2roc

Resample precision-recall curves correctly!

Language: Jupyter Notebook - Size: 179 KB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 1 - Forks: 0