A porting to modern g++ and C+11 of the IBM Quest dataset generator

Decision Tree project based on ID3 Algorithm built on Jupytor Notebook with Python. Dataset taken: Tennis.csv

This is projects of Data Mining

Market basket analysis is a technique used mostly by retailers to identify which products clients purchase together most frequently. This involves analyzing point of sale (POS) transaction data to identify the correlations between different items according to their co-occurrence in the data.

Code for the paper "SPEck: Mining Statistically-significant Sequential Patterns Efficiently with Exact Sampling", by Steedman Jenkins, Stefan Walzer-Goldfeld, and Matteo Riondato, appearing in the Data Mining and Knowledge Discovery Special Issue for ECML PKDD'22.

Association Rule Mining Using FP-Growth & ANN Techniques

A project for streaming algorithms: Bloom filtering, Flajolet-Martin Algorithm, Fixed-Size Sampling

Practice codes for Machine Learning, Data Mining and NLP in Python

The project's objective is to harness a HR Analytics dataset. With predictive proccess I tried to equip HR management with actionable insights, enabling them to proactively address attrition issues and implement targeted retention strategies.

Python Implementation of data mining algorithms(Apriori, Eclact, FP Growth ).

一些数据挖掘算法

A data mining project using the Apriori algorithm for Market Basket Analysis. Association rules were generated and interpreted across various parameter settings to discover purchasing patterns in retail transaction data.

This contains all projects that I have done during my master degree.

The project or work which goals to extract the opinions, emotions, attitudes of public towards different object of interest. Sentiment analysis is a form of shallow semantic analysis of texts. In the project an automatic approach that involves supervised machine learning and text mining classification algorithms are used which includes the senti…

This repository contains a reference implementation of Range–CoMine (single‑pass colocation mining for a distance range) and two baselines (Naive and RangeInc‑Mining). It is designed for clarity and correctness on small–medium datasets.

The code of ICML 2024 ''Decouple then Classify: A Dynamic Multi-view Labeling Strategy with Shared and Specific Information''

Implementing Gaussian Naive Bayes and KNN from scratch and evaluating their performances on heart dataset

This Repository contains the Intermediate level of programing code that are used in Data mining, e.t.c for Understanding of Algorithms and various other tasks.

Course Notes