Explore MATLAB source code curated for "数据集" with clean implementations, documentation, and examples.
A MATLAB-based handwritten digit recognition program utilizing minimum Euclidean distance classification. The dataset is sourced from UCI Machine Learning Repository, featuring comprehensive performance evaluation metrics including accuracy, recall, and F1-score calculations with code implementation insights.
Implementation of Particle Swarm Optimization for Solving Traveling Salesman Problem, Including Dataset and Demonstrating Robust Performance Results
The Partial Least Squares (PLS) method refers to performing principal component analysis for dimensionality reduction on datasets before conducting linear regression analysis based on least squares. The following source code is provided in its complete form by the GreenSim team for free use, with proper attribution required to GreenSim team (http://blog.sina.com.cn/greensim). The implementation includes key components for covariance maximization and projection calculations.
A MATLAB-based pedestrian detection code collection utilizing Haar features and SVM, including comprehensive dataset for testing and training.
Implementation of the classic LDA feature selection algorithm using MATLAB, including complete dataset for practical experimentation and validation
Implementation of continuous attribute discretization algorithms in rough set theory using MATLAB, including ready-to-use datasets for testing and analysis.
MATLAB implementation of k-means clustering algorithm with included test datasets for performance evaluation and testing purposes.
Visualize MNIST dataset images with code implementation examples to enhance understanding of the handwritten digit data structure and characteristics.
This implementation covers both user-based and item-based collaborative filtering approaches (detailed in README) using the provided dataset for training and evaluation.
Hand Gesture Recognition Implementation with Algorithm Flowcharts and MATLAB Codebase - Featuring American Sign Language (ASL) Detection with Background Preprocessing Requirements