文件名称:Classification-MatLab-Toolbox

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  • 其他小程序
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2016-09-23
  • 文件大小:
  • 705kb
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  • 0次
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  • 仨*
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matlab工具箱,包括SVM,ICA,PCA,NN等等模式识别算法,很有参考价值--attern recognition Matlab toolbox, including SVM, ICA, PCA, NN pattern recognition algorithms, and so on, of great reference value
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下载文件列表





Classification MatLab Toolbox

.............................\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

.............................\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

...........

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