模式分类的相关算法代码，例如：高斯混合模型、k均值聚类、最大似然、贝叶斯、MPKPCA、MICA、概率密度、遗传算法、SVM等

所有关于模式分类的方法的介绍和代码的使用，包括高斯混合模型、k均值聚类、最大似然、贝叶斯、MPKPCA、MICA、概率密度、遗传算法、SVM等，十分适用于做算法和图像等方面的下载学习

About.bmp
Ada_Boost.m
ADDC.m
AGHC.m
Backpropagation_Batch.m
Backpropagation_CGD.m
Backpropagation_Quickprop.m
Backpropagation_Recurrent.m
Backpropagation_SM.m
Backpropagation_Stochastic.m
Balanced_Winnow.m
Bayesian_Model_Comparison.m
Bhattacharyya.m
BIMSEC.m
C4_5.m
calculate_error.m
calculate_region.m
CART.m
CARTfunctions.m
Cascade_Correlation.m
Chernoff.m
Classification.txt
classification_error.m
classifier.m
classifier.mat
classifier_commands.m
click_points.m
Competitive_learning.m
Components_without_DF.m
Components_with_DF.m
contents.m
README.txt
Deterministic_annealing.m
Deterministic_Boltzmann.m
Deterministic_SA.m
Discrete_Bayes.m
Discriminability.m
DSLVQ.m
EM.m
enter_distributions.m
enter_distributions.mat
enter_distributions_commands.m
feature_selection.m
feature_selection.mat
Feature_selection.txt
feature_selection_commands.m
FindParameters.m
FindParameters.mat
FindParametersFunctions.m
NLCA.m
FishersLinearDiscriminant.m
fuzzy_k_means.m
GaussianParameters.m
GaussianParameters.mat
generate_data_set.m
Genetic_Algorithm.m
Genetic_Culling.m
Genetic_Programming.m
Gibbs.m
HDR.m
high_histogram.m
Ho_Kashyap.m
ICA.m
ID3.m
Infomat.m
Interactive_Learning.m
Kohonen_SOFM.m
synthetic.mat
k_means.m
Leader_Follower.m
LMS.m
load_file.m
Local_Polynomial.m
LocBoost.m
LocBoostFunctions.m
loglikelihood.m
LS.m
LVQ1.m
LVQ3.m
make_a_draw.m
Marginalization.m
MDS.m
Minimum_Cost.m
min_spanning_tree.m
ML.m
ML_diag.m
ML_II.m
multialgorithms.m
multialgorithms.mat
multialgorithms_commands.m
Multivariate_Splines.m
NDDF.m
NearestNeighborEditing.m
Nearest_Neighbor.m
None.m
Optimal_Brain_Surgeon.m
Parzen.m
PCA.m
Perceptron.m
Perceptron_Batch.m
Perceptron_BVI.m
Perceptron_FM.m
Perceptron_VIM.m
plot_process.m
plot_scatter.m
PNN.m
Pocket.m
predict_performance.m
Preprocessing.txt
process_params.m
Projection_Pursuit.m
RBF_Network.m
RCE.m
RDA.m
read_algorithms.m
Relaxation_BM.m
Relaxation_SSM.m
SOHC.m
start_classify.m
Stochastic_SA.m
Store_Grabbag.m
Stumps.m
SVM.m
classify_paramteric.m
voronoi_regions.m
MultipleDiscriminantAnalysis.m
datasets
XOR.mat
clouds.mat
chess.mat
four_spiral.mat
spiral.mat
DHS_cover.mat
DHSchapter5.mat
DHSchapter3.mat
DHSchapter4.mat
DHSchapter2.mat
DHSchapter6.mat
DHSchapter7.mat
DHSchapter8.mat
DHSchapter9.mat
DHSchapter10.mat
Other
Bayesian_Belief_Networks.m
Bayesian_parameter_est.m
Bayes_belief_net.mat
Bottom_Up_Parsing.m
Boyer_Moore_String_Matching.m
contents.m
demo_fun.m
Edit_Distance.m
gradient_descent.m
Grammatical_Inference.m
high_histogram.m
HMM_Backward.m
HMM_Boltzmann.m
HMM_Decoding.m
HMM_Evaluation.m
HMM_Forward.m
HMM_Forward_Backward.m
HMM_generate.m
mean_bootstrap.m
mean_jackknife.m
Naive_String_Matching.m
Newton_descent.m
ROCC.m
sample_hmm.mat
Stochastic_Regression.m
sufficient_statistics.m
Whitening_transform.m
Scaling_transform.m
show_algorithms.m
Sequential_Feature_Selection.m
Exhaustive_Feature_Selection.m
combinations.m
Information_based_selection.m
Perceptron_Voted.m