文件名称:MLcode
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Windows] [Linux] [Python] [源码]
- 上传时间：
- 2012-11-26
- 文件大小：
- 95kb
- 下载次数：
- 0次
- 提 供 者：
- jings******
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
这是关于机器学习的经典例程，只有你想不到的，没有你做不到的。即可用来学习，也可参考来写论文。包含几乎所有机器学习的相关内容。-This is the classic routines on machine learning, and only you can not think, no you can not do. Can be used to learn, but also can refer to write papers. Almost all machine learning contains relevant content.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
MLcode\Machine Learning\src\10 Dimension Reduction\ecoli.py
......\................\...\......................\factoranalysis.py
......\................\...\......................\floyd.py
......\................\...\......................\iris.py
......\................\...\......................\isomap.py
......\................\...\......................\kernelpca.py
......\................\...\......................\kpcademo.py
......\................\...\......................\lda.py
......\................\...\......................\lle.py
......\................\...\......................\pca.py
......\................\...\......................\pcademo.py
......\................\...\10 Dimension Reduction
......\................\...\.1 Optimisation\CG.py
......\................\...\...............\LevenbergMarquardt.py
......\................\...\...............\LevenbergMarquardt_leastsq.py
......\................\...\...............\Newton.py
......\................\...\...............\steepest.py
......\................\...\...............\TSP.py
......\................\...\11 Optimisation
......\................\...\.2 Evolutionary\exhaustiveKnapsack.py
......\................\...\...............\fourpeaks.py
......\................\...\...............\ga.py
......\................\...\...............\greedyKnapsack.py
......\................\...\...............\knapsack.py
......\................\...\...............\PBIL.py
......\................\...\...............\run_ga.py
......\................\...\12 Evolutionary
......\................\...\.3 Reinforcement\SARSA.py
......\................\...\................\SARSA_cliff.py
......\................\...\................\TDZero.py
......\................\...\................\TDZero_cliff.py
......\................\...\13 Reinforcement
......\................\...\.4 MCMC\BoxMuller.py
......\................\...\.......\Gibbs.py
......\................\...\.......\importancesampling.py
......\................\...\.......\lcg.py
......\................\...\.......\MH.py
......\................\...\.......\rejectionsampling.py
......\................\...\.......\SIR.py
......\................\...\14 MCMC
......\................\...\.5 Graphical Models\Gibbs.py
......\................\...\...................\graphdemo.py
......\................\...\...................\HMM.py
......\................\...\...................\Kalman.py
......\................\...\...................\MRF.py
......\................\...\...................\world.png
......\................\...\15 Graphical Models
......\................\...\2 Linear\auto-mpg.py
......\................\...\........\linreg.py
......\................\...\........\linreg_logic_eg.py
......\................\...\........\logic.py
......\................\...\........\pcn.py
......\................\...\........\pcn_logic_eg.py
......\................\...\........\pima.py
......\................\...\2 Linear
......\................\...\3 MLP\iris.py
......\................\...\.....\iris_proc.data
......\................\...\.....\logic.py
......\................\...\.....\mlp.py
......\................\...\.....\PNoz.dat
......\................\...\.....\PNOz.py
......\................\...\.....\sinewave.py
......\................\...\3 MLP
......\................\...\4 RBF\iris.py
......\................\...\.....\least_squares.py
......\................\...\.....\rbf.py
......\................\...\4 RBF
......\................\...\6 Trees\dtree.py
......\................\...\.......\party.data
......\................\...\.......\party.py
......\................\...\6 Trees
......\................\...\7 Committee\bagging.py
......\................\...\...........\boost.py
......\................\...\...........\car.data
......\................\...\...........\car.py
......\................\...\...........\dtw.py
......\................\...\...........\party.py
......\................\...\7 Committee
......\................\...\8 Probability\gaussian.py
......\................\...\.............\GMM.py
....
......\................\...\......................\factoranalysis.py
......\................\...\......................\floyd.py
......\................\...\......................\iris.py
......\................\...\......................\isomap.py
......\................\...\......................\kernelpca.py
......\................\...\......................\kpcademo.py
......\................\...\......................\lda.py
......\................\...\......................\lle.py
......\................\...\......................\pca.py
......\................\...\......................\pcademo.py
......\................\...\10 Dimension Reduction
......\................\...\.1 Optimisation\CG.py
......\................\...\...............\LevenbergMarquardt.py
......\................\...\...............\LevenbergMarquardt_leastsq.py
......\................\...\...............\Newton.py
......\................\...\...............\steepest.py
......\................\...\...............\TSP.py
......\................\...\11 Optimisation
......\................\...\.2 Evolutionary\exhaustiveKnapsack.py
......\................\...\...............\fourpeaks.py
......\................\...\...............\ga.py
......\................\...\...............\greedyKnapsack.py
......\................\...\...............\knapsack.py
......\................\...\...............\PBIL.py
......\................\...\...............\run_ga.py
......\................\...\12 Evolutionary
......\................\...\.3 Reinforcement\SARSA.py
......\................\...\................\SARSA_cliff.py
......\................\...\................\TDZero.py
......\................\...\................\TDZero_cliff.py
......\................\...\13 Reinforcement
......\................\...\.4 MCMC\BoxMuller.py
......\................\...\.......\Gibbs.py
......\................\...\.......\importancesampling.py
......\................\...\.......\lcg.py
......\................\...\.......\MH.py
......\................\...\.......\rejectionsampling.py
......\................\...\.......\SIR.py
......\................\...\14 MCMC
......\................\...\.5 Graphical Models\Gibbs.py
......\................\...\...................\graphdemo.py
......\................\...\...................\HMM.py
......\................\...\...................\Kalman.py
......\................\...\...................\MRF.py
......\................\...\...................\world.png
......\................\...\15 Graphical Models
......\................\...\2 Linear\auto-mpg.py
......\................\...\........\linreg.py
......\................\...\........\linreg_logic_eg.py
......\................\...\........\logic.py
......\................\...\........\pcn.py
......\................\...\........\pcn_logic_eg.py
......\................\...\........\pima.py
......\................\...\2 Linear
......\................\...\3 MLP\iris.py
......\................\...\.....\iris_proc.data
......\................\...\.....\logic.py
......\................\...\.....\mlp.py
......\................\...\.....\PNoz.dat
......\................\...\.....\PNOz.py
......\................\...\.....\sinewave.py
......\................\...\3 MLP
......\................\...\4 RBF\iris.py
......\................\...\.....\least_squares.py
......\................\...\.....\rbf.py
......\................\...\4 RBF
......\................\...\6 Trees\dtree.py
......\................\...\.......\party.data
......\................\...\.......\party.py
......\................\...\6 Trees
......\................\...\7 Committee\bagging.py
......\................\...\...........\boost.py
......\................\...\...........\car.data
......\................\...\...........\car.py
......\................\...\...........\dtw.py
......\................\...\...........\party.py
......\................\...\7 Committee
......\................\...\8 Probability\gaussian.py
......\................\...\.............\GMM.py
....