文件名称:class_toolbox
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maltab分类工具箱,整合了各种经典算法,在这些算法的帮助下有助于设计分类方法实验。-The classification toolbox is a list of functions for supervised and
unsupervised classification algorithms. These algorithms help design categorization
methods for experimental as well as synthetic data,
unsupervised classification algorithms. These algorithms help design categorization
methods for experimental as well as synthetic data,
(系统自动生成,下载前可以参看下载内容)
下载文件列表
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
User guide.pdf
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
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
synthetic.mat
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/
datasets/XOR.mat
datasets/clouds.mat
datasets/chess.mat
datasets/four_spiral.mat
datasets/spiral.mat
datasets/DHS_cover.mat
datasets/DHSchapter5.mat
datasets/DHSchapter3.mat
datasets/DHSchapter4.mat
datasets/DHSchapter2.mat
datasets/DHSchapter6.mat
datasets/DHSchapter7.mat
datasets/DHSchapter8.mat
datasets/DHSchapter9.mat
datasets/DHSchapter10.mat
Other/
Other/Bayesian_Belief_Networks.m
Other/Bayesian_parameter_est.m
Other/Bayes_belief_net.mat
Other/Bottom_Up_Parsing.m
Other/Boyer_Moore_String_Matching.m
Other/contents.m
Other/demo_fun.m
Other/Edit_Distance.m
Other/gradient_descent.m
Other/Grammatical_Inference.m
Other/high_histogram.m
Other/HMM_Backward.m
Other/HMM_Boltzmann.m
Other/HMM_Decoding.m
Other/HMM_Evaluation.m
Other/HMM_Forward.m
Other/HMM_Forward_Backward.m
Other/HMM_generate.m
Other/mean_bootstrap.m
Other/mean_jackknife.m
Other/Naive_String_Matching.m
Other/Newton_descent.m
Other/ROCC.m
Other/sample_hmm.mat
Other/Stochastic_Regression.m
Other/sufficient_statistics.m
Other/synthetic.mat
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
Matlab中文论坛--助努力的人完成毕业设计.url
使用帮助:新手必看.htm
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
User guide.pdf
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
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
synthetic.mat
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/
datasets/XOR.mat
datasets/clouds.mat
datasets/chess.mat
datasets/four_spiral.mat
datasets/spiral.mat
datasets/DHS_cover.mat
datasets/DHSchapter5.mat
datasets/DHSchapter3.mat
datasets/DHSchapter4.mat
datasets/DHSchapter2.mat
datasets/DHSchapter6.mat
datasets/DHSchapter7.mat
datasets/DHSchapter8.mat
datasets/DHSchapter9.mat
datasets/DHSchapter10.mat
Other/
Other/Bayesian_Belief_Networks.m
Other/Bayesian_parameter_est.m
Other/Bayes_belief_net.mat
Other/Bottom_Up_Parsing.m
Other/Boyer_Moore_String_Matching.m
Other/contents.m
Other/demo_fun.m
Other/Edit_Distance.m
Other/gradient_descent.m
Other/Grammatical_Inference.m
Other/high_histogram.m
Other/HMM_Backward.m
Other/HMM_Boltzmann.m
Other/HMM_Decoding.m
Other/HMM_Evaluation.m
Other/HMM_Forward.m
Other/HMM_Forward_Backward.m
Other/HMM_generate.m
Other/mean_bootstrap.m
Other/mean_jackknife.m
Other/Naive_String_Matching.m
Other/Newton_descent.m
Other/ROCC.m
Other/sample_hmm.mat
Other/Stochastic_Regression.m
Other/sufficient_statistics.m
Other/synthetic.mat
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
Matlab中文论坛--助努力的人完成毕业设计.url
使用帮助:新手必看.htm
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