Data mining algorithms for classification MATLAB source code.

Classification MatLab Toolbox\spiral.mat
.............................\ADDC.m
.............................\AGHC.m
.............................\load_file.m
.............................\About.bmp
.............................\make_a_draw.m
.............................\Ada_Boost.m
.............................\BIMSEC.m
.............................\feature_selection.m
.............................\Backpropagation_Batch.m
.............................\feature_selection.mat
.............................\Backpropagation_CGD.m
.............................\enter_distributions_commands.m
.............................\Backpropagation_Quickprop.m
.............................\feature_selection_commands.m
.............................\Backpropagation_Recurrent.m
.............................\find_classes.m
.............................\Backpropagation_SM.m
.............................\fuzzy_k_means.m
.............................\Backpropagation_Stochastic.m
.............................\generate_data_set.m
.............................\Balanced_Winnow.m
.............................\high_histogram.m
.............................\Bayesian_Model_Comparison.m
.............................\loglikelihood.m
.............................\Bhattacharyya.m
.............................\C4_5.m
.............................\CART.m
.............................\min_spanning_tree.m
.............................\CARTfunctions.m
.............................\multialgorithms.m
.............................\Cascade_Correlation.m
.............................\seperable.mat
.............................\Chernoff.m
.............................\multialgorithms.mat
.............................\Classification.txt
.............................\multialgorithms_commands.m
.............................\Competitive_learning.m
.............................\plot_process.m
.............................\Components_with_DF.m
.............................\plot_scatter.m
.............................\Components_without_DF.m
.............................\DSLVQ.m
.............................\predict_performance.m
.............................\Deterministic_Boltzmann.m
.............................\process_params.m
.............................\Deterministic_SA.m
.............................\read_algorithms.m
.............................\Deterministic_annealing.m
.............................\start_classify.m
.............................\Discrete_Bayes.m
.............................\voronoi_regions.m
.............................\Discriminability.m
.............................\EM.m
.............................\Other\Bayes_belief_net.mat
.............................\.....\Bayesian_Belief_Networks.m
.............................\.....\Bayesian_parameter_est.m
.............................\.....\Bottom_Up_Parsing.m
.............................\.....\Boyer_Moore_String_Matching.m
.............................\.....\Edit_Distance.m
.............................\.....\Grammatical_Inference.m
.............................\.....\HMM_Backward.m
.............................\.....\HMM_Boltzmann.m
.............................\.....\HMM_Decoding.m
.............................\.....\HMM_Evaluation.m
.............................\.....\HMM_Forward.m
.............................\.....\HMM_Forward_Backward.m
.............................\.....\HMM_generate.m
.............................\.....\MultipleDiscriminantAnalysis.m
.............................\.....\Naive_String_Matching.m
.............................\.....\Newton_descent.m
.............................\.....\ROCC.m
.............................\.....\Stochastic_Regression.m
.............................\.....\contents.m
.............................\.....\demo_fun.m
.............................\.....\gradient_descent.m
.............................\.....\high_histogram.m
.............................\.....\mean_bootstrap.m
.............................\.....\mean_jackknife.m
.............................\.....\sample_hmm.mat
.............................\.....\sufficient_statistics.m
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