Description: Data Mining matlab source, including the field of classical machine learning algorithms such as ID3, C4.5, NN, CARD, EM, etc..
- [myMatlabfenlei] - Matlab on the classification of data min
- [ID3(MATLAB).Rar] - classic with Matlab prepared by the ID3
- [C4.5_Kidney] - cases from the hospital to obtain the da
- [ID3C4.5] - ID3 C4.5 of the source. Data Mining for
- [DS] - ds realize data fusion theory of evidenc
- [C4_5] - Matlab language used to write the C4.5 a
- [c4.5matlab] - c4.5 decision tree decision tree on the
- [DecisionTrees] - this is decision tree ID3 algorithm, thi
- [C4.5] - good
- [matlab-C4.5] - C4.5 decision tree
File list (Check if you may need any files):
mitmatlab
.........\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
.........\chess.mat
.........\Classification.txt
.........\classification_error.m
.........\classifier.m
.........\classifier.mat
.........\classifier_commands.m
.........\click_points.m
.........\clouds.mat
.........\Competitive_learning.m
.........\Components_without_DF.m
.........\Components_with_DF.m
.........\contents.m
.........\decision_region.m
.........\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
.........\find_classes.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.asv
.........\ID3.m
.........\index(1).htm
.........\index.htm
.........\Infomat.m
.........\Interactive_Learning.m
.........\Kohonen_SOFM.m
.........\Koller.m
.........\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
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