New Data Mining Methods: Support Vector Machine Algorithm Examples
This book provides practical algorithm examples for Support Vector Machines, offering valuable learning assistance with code implementation demonstrations.
Fuzzy K-Means Algorithm in Data Mining
Implementation of Fuzzy K-Means Algorithm for Data Mining Using MATLAB
MATLAB Implementation of Classic Algorithms in Data Mining
Comprehensive collection of MATLAB code implementations for fundamental data mining algorithms
Data Mining MATLAB Source Code Collection
A comprehensive MATLAB source code repository containing classic machine learning algorithms including ID3, C4.5, Neural Networks, CARD, and EM algorithms for data mining applications.
Data Mining Classification Algorithms for MATLAB Implementation
MATLAB implementations of popular data mining classification algorithms including ID3, C4.5, CART, and SLIQ - all thoroughly debugged and ready to run. Recommended for download and practical use in classification projects.
CART Data Mining Decision Tree Algorithm Implementation in MATLAB
Implementation of CART data mining decision tree algorithm using MATLAB with complete code structure and algorithm explanations
MATLAB Code for Calculating KL Divergence in Data Mining Applications
Implementation of KL divergence computation in MATLAB environment for measuring probability distribution differences in data mining tasks
ID3 and C4.5 Algorithms Source Code
Source code implementation of ID3 and C4.5 decision tree algorithms for data mining applications, featuring entropy calculations and information gain optimization.
Cloud Model Generator
Cloud Model Generator comprises fundamental cloud generators, X-conditional cloud generators, and Y-conditional cloud generators, currently applied in foundational domains like data mining with implementations involving forward and backward cloud algorithms for uncertainty modeling.
A Data Mining Program for Data Warehouse Implementation
A MATLAB-based data mining program designed for data warehouse applications, featuring efficient algorithms and practical usability for data analysis tasks.