[IEEE T-KDE 2026] Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).

ELKI Data Mining Toolkit

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

A package that makes it trivial to create and evaluate machine learning pipeline architectures.

A graph data science library for Rust 🦀 with Python bindings 🐍

TSrepr: R package for time series representations

Simple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN

A Python implementation of divisive and hierarchical clustering algorithms. The algorithms were tested on the Human Gene DNA Sequence dataset and dendrograms were plotted.

A memory efficient GBDT on adaptive distributions. Much faster than LightGBM with higher accuracy. Implicit merge operation.

Implementation of the Apriori and Eclat algorithms, two of the best-known basic algorithms for mining frequent item sets in a set of transactions, implementation in Python.

Data Mining Algorithms with C# using LINQ

A Python implementation of Naive Bayes from scratch.

GSP (Generalized Sequence Pattern) algorithm in Python

Programs of BE Computer Engineering 2012 Pattern

Awesome Semi-supervised Multi-view Classification is a collection of SOTA, novel semi-supervised multi-view classification methods (papers, codes).

Implementation of FPTree-Growth and Apriori-Algorithm for finding frequent patterns in Transactional Database.

Awesome Continual Multi-view Clustering is a collection of SOTA, novel continual multi-view clustering methods (papers, codes).

scSurvival is a new tool for survival analysis from single cell cohort dataset.

📊 数据挖掘常用算法：关联分析Apriori算法，数据分类决策树算法，数据聚类K-means算法

Data Mining algorithms for IDMW632C course at IIIT Allahabad, 6th semester