smote

nickkunz/smogn

Synthetic Minority Over-Sampling Technique for Regression

tgsmith61591/smrt

Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.

damianhorna/multi-imbalance

Python package for tackling multi-class imbalance problems. http://www.cs.put.poznan.pl/mlango/publications/multiimbalance/

zunicd/Bank-Churn-Prediction

Bank customers churn dashboard with predictions from several machine learning models.

jiangnanboy/spark_data_mining

spark tutorial for big data mining。包括app流量运营分析、als推荐、smote样本采样、RFM客户价值分群、AHP层次分析客户价值得分、手机定位数据商圈挖掘、马尔可夫智能邮件预测、时序预测、关联规则、推荐电影好友等。

kaushalshetty/SMOTE

Synthetic Minority Over-sampling Technique

SudhakarKuma/Machine_Learning

A repository of resources for understanding the concepts of machine learning/deep learning. 

bhattbhavesh91/imbalance_class_sklearn

Address imbalance classes in machine learning projects.

hk-mp5a3/Class-Imbalance

Dealing with class imbalance problem in machine learning. Synthetic oversampling(SMOTE, ADASYN).

georgedouzas/geometric-smote

Implementation of the Geometric SMOTE over-sampling algorithm.

LaurentVeyssier/Credit-Card-fraud-detection-using-Machine-Learning

Detect Fraudulent Credit Card transactions using different Machine Learning models and compare performances

devrajkataria/Credit-Card-Fraud-Detection-ML-WebApp

timeamagyar/kdd-cup-99-python

Analysis and preprocessing of the kdd cup 99 dataset using python and scikit-learn

navneetkrc/Deep-Learning-Experiments-implemented-using-Google-Colab

Colab Compatible FastAI notebooks for NLP and Computer Vision Datasets

mjuez/approx-smote

Approx-SMOTE: fast SMOTE for Big Data on Apache Spark

atif-hassan/Regression_ReSampling

A python library for repurposing traditional classification-based resampling techniques for regression tasks

earthat/Automatic-Digital-Modulation-Detection-

This repository presents the code for digital modulation detection in Communication networks

MatteoM95/Default-of-Credit-Card-Clients-Dataset-Analisys

Analysis and classification using machine learning algorithms on the UCI Default of Credit Card Clients Dataset.

nive927/Flight_Delay_Prediction

A two-stage predictive machine learning engine that forecasts the on-time performance of flights for 15 different airports in the USA based on data collected in 2016 and 2017.

bcbi/ClassImbalance.jl

Sampling-based methods for correcting for class imbalance in two-category classification problems

ai-se/Smote_tune

ICSE'18: Tuning Smote

fischlerben/Machine-Learning-Credit-Risk

Machine-Learning project that uses a variety of credit-related risk factors to predict a potential client's credit risk. Machine Learning models include Logistic Regression, Balanced Random Forest and EasyEnsemble, and a variety of re-sampling techniques are used (Oversampling/SMOTE, Undersampling/Cluster Centroids, and SMOTEENN) to re-sample the data. Evaluation metrics like the accuracy score, classification report and confusion matrix are generated to compare models and determine which suits this particular set of data best.

ireneliu521/Credit-Card-Fraud_J2D_Project_Python

Apply 7 common Machine Learning Algorithms to detect fraud, while dealing with imbalanced dataset

shuLhan/go-mining

Data mining with Go.

ashomah/HR-Analytics

HR Analytics Dataset

rikhuijzer/Resample.jl

An implementation of SMOTE

sonnguyen129/Accident-Severity-Prediction

Predicting the severity of accident

Ashutosh27ind/PGDDS-Capstone-Project

Credit Card Fraud Detection Project

earthat/SMOTE-over-Sampling

This repository is for MATLAB code for balancing of multiclass data by SMOTE

basiralab/MV-LEAP

Multi-View LEArning-based data Proliferator (MV-LEAP) for boosting classification using highly imbalanced classes.

bayhaqy/analisa-sentimen

Application fo sentiment analysis using VADER and Support Vector Machine (SVM) with SMOTE

cedoula/Credit_Risk_Analysis

Build and evaluate several machine learning algorithms to predict credit risk.

desininja/voice-disorder

Data Science project. ML algorithms to detect voice disorders.

swordspoet/UCI_imbalanced_data

The machine learning project on UCI imbalanced data.

antorguez95/synthetic_data_generation_framework

This repository contains the code of our published work in IEEE JBHI. Our main objective was to demonstrate the feasibility of the use of synthetic data to effectively train Machine Learning algorithms, prooving that it benefits classification performance most of the times.