MATLAB Rough Set Attribute Reduction Program with Detailed Code Implementation
A MATLAB implementation of rough set attribute reduction algorithm featuring comprehensive code annotations and detailed explanations of the computational approach
Rough Set-based Feature Selection with MATLAB Implementation
MATLAB source code for implementing feature selection algorithms based on rough set theory, including core data structures and attribute reduction functions.
MATLAB Implementation of Rough Set Algorithms for Data Reduction
Data Reduction Techniques Using Fuzzy Rough Sets and Fuzzy Mutual Information with Implementation Approaches - Feature Evaluation and Selection Based on Fuzzy Preference Rough Set Methods
MATLAB Implementation of Rough Set Theory
This MATLAB code collection for rough set computation contains multiple files addressing different scenarios, including core algorithms for attribute reduction, dependency degree calculation, and rule extraction from decision tables.
Rough Set Conditional Attribute Dependency Degree Calculation Function for Decision Attributes
User-friendly dependency degree calculation function for conditional attributes on decision attributes based on rough set theory, featuring clear algorithmic implementation and practical code integration.
Rough Set Attribute Reduction and Discretization
Rough set attribute reduction and discretization with rule extraction methodology explained
Complete MATLAB Program for Rough Set Attribute Reduction Using Different Methods
Complete MATLAB program implementing various rough set attribute reduction techniques including positive region approximation, entropy-based methods, and genetic algorithm approaches with full code implementation and detailed explanations.
Rough Set Attribute Reduction with Practical Examples
Attribute reduction methodology based on rough set theory, featuring practical implementation examples and enhanced code-related explanations for better understanding
Algorithm for Rough Set Attribute Reduction
This program implements the rough set attribute reduction algorithm with efficient computational approaches! Researchers working in this field are encouraged to download and explore its implementation.
PCA+LDA+Rough Set+Fuzzy Neural Network Implementation for ORL Face Image Processing
This package contains 5 MATLAB codes implementing a comprehensive face recognition pipeline: 1) saveORLimage.m divides ORL face database into test set (ptest) and training set (pstudy), saved as imagedata.mat; 2) savelda.m performs PCA dimensionality reduction followed by LDA feature extraction, generating new test set (ldatest) and training set (ldastudy) saved as imageldadata.mat; 3) discretimage.m discretizes ldastudy data into discrete matrix disdata, stored as imagedisdata.mat; 4) savers.m constructs decision tables from disdata