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,

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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

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