19854816mitmatlab Include pattern recognition wher

Title: 19854816mitmatlab

Category:
AI-NN-PR
Tags:
[Matlab] [源码]
File Size:
636kb
Update:
2012-11-26
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Uploaded by:
zoukuicj

Description: Include pattern recognition where a lot of function implementation, classifier, KNN algorithm, useful for learners

Downloaders recently: [More information of uploader zoukuicj]

To Search: knn mitmatlab

[knn] - k nearest neiborhood in macine learning
[fknn-fxtoolbox] - FKNN: Fuzzy KNN classification algorithm
[knn] - KNN K-nearest neighbor rule for classifi
[ModuleReconizeKNNalgorithm] - KNN is an effective pattern recognition
[mill] - Contains a lot of classification algorit
[SVM_luzhenbo] - Four support vector machines for pattern
[moshishibietongjifangfatoolbox] - Pattern recognition of various calculati
[Whole_Between] - KNN classifier, this classifier in the a
[knn] - k neighbor problem, I do, the effect is
[knn] - failed to translate

File list (Check if you may need any files):

mitmatlab\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
.........\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.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
.........\NLPCA.m
.........\None.m