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awesome-imbalanced-learning

A curated list of awesome imbalanced learning papers, codes, frameworks, and libraries. | 类别不平衡学习：论文、代码、框架与库

data-preprocessing-project-imbalanced-classes-problem

Data Preprocessing Project - Imbalanced classes problem

deep-belief-network-and-logistic-regression-for-software-fault-prediction

Recreation of "Deep Learning for Just-In-Time Defect Prediction"

deep-learning-cnn

dnn-based-software-defect-prediction

experimental data and code

fault-prediction-using-nasa-mdp-dataset

Identifying the best algorithm for defect prediction in softwares and providing the most accurate results. The Metrics Data Program dataset provided by NASA has been used.

fraud_detection

Fraud Detection with or without Oversampling

gan_oversampling

Master's thesis: an application of Generative Adversarial Network to imbalanced datasets.

ganbasedoversampling

handle-imbalanced-dataset

handling-imbalanced-dataset

Quick notebook to refer to different ways to handle imbalanced datasets.

imbalanced-algorithms

Python-based implementations of algorithms for learning on imbalanced data.

imbalanced-data

Examples of algorithms dealing with imbalanced data.

imbalanced-dataset-sampler

A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.

imbsdp

Imbalanced learning for software defect prediction

loras

Localized Randomized Affine Shadowsampling (LoRAS) oversampling technique

neural-networks-and-deep-learning

This is my assignment on Andrew Ng's course “neural networks and deep learning”

numerical-data-classifier-using-cnn

pc1-software-defect-classification-and-prediction

pca-ann

Defects in a computer program are predicted using ANN and Dimensionality Reduction Technique like PCA and then training a classifier hence comparing both the techniques.

promise20-defectpredictiontreeensembles

Repository for "Software Defect Prediction Using Tree-based Ensembles" published in 16th ACM International Conference on Predictive Modeling in Software Engineering (PROMISE 20)

smote_variants

A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features

software-defect-prediction

Application of Deep Learning and Feature Extraction in Software Defect Prediction

software-defect-prediction-cnn-and-rnn

Software defect prediction using recurrent neural network and convolutional neural network

software-defect-prediction-using-machine-learnig-and-deep-learning

software-defects-prediction

software_defect_prediction

Software defect prediction using ensemble learning

softwaredefectprediction

softwaredefectprediction-1

softwarefaultprediction

we proposed a software defect predictive development models using machine learning techniques that can enable the software to continue its projected task.