-PRML一书中机器学习算法的Matlab代码.zip

Introduction ------- This Matlab package implements machine learning algorithms described in the great textbook: Pattern Recognition and Machine Learning by C. Bishop ([PRML](http://research.microsoft.com/en-us/um/people/cmbishop/prml/)). It is written purely in Matlab language. It is self-contained. There is no external dependency. Note: this package requires Matlab **R2016b** or latter, since it utilizes a new Matlab syntax called [Implicit expansion](https://cn.mathworks.com/help/matlab/release-notes.html?rntext=implicit+expansion&startrelease=R2016b&endrelease=R2016b&groupby=release&sortby=descending) (a.k.a. broadcasting). It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). Design Goal ------- * Succinct: The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. * Efficient: Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). * Robust: Many tricks for numerical stability are applied, such as computing probability in logrithm domain, square root matrix update to enforce matrix symmetry\PD, etc. * Readable: The code is heavily commented. Corresponding formulas in PRML are annoted. Symbols are in sync with the book. * Practical: The package is not only readable, but also meant to be easily used and modified to facilitate ML research. Many functions in this package are already widely used (see [Matlab file exchange](http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A49739)). Installation ------- 1. Download the package to a local folder (e.g. ~/PRMLT/) by running: ```console git clone https://github.com/PRML/PRMLT.git ``` 2. Run Matlab and navigate to the folder (~/PRMLT/), then run the init.m script. 3. Run some demos in ~/PRMLT/demo folder. Enjoy! FeedBack ------- If you find any bug or have any suggestion, please do file issues. I am graceful for any feedback and will do my best to improve this package. License ------- Released under MIT license Contact ------- sth4nth at gmail dot com