代码搜索:Learning

找到约 5,352 项符合「Learning」的源代码

代码结果 5,352
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m rbf_network.m

function [D, mu, Wo] = RBF_Network(train_features, train_targets, Nh, region) % Classify using a backpropagation network with a batch learning algorithm % Inputs: % features- Train features % t
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m backpropagation_batch.m

function [test_targets, Wh, Wo, J] = Backpropagation_Batch(train_patterns, train_targets, test_patterns, params) % Classify using a backpropagation network with a batch learning algorithm % Inputs
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m backpropagation_quickprop.m

function [test_targets, Wh, Wo, J] = Backpropagation_Quickprop(train_patterns, train_targets, test_patterns, params) % Classify using a backpropagation network with a batch learning algorithm and q
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m backpropagation_cgd.m

function [test_targets, Wh, Wo, errors] = Backpropagation_CGD(train_patterns, train_targets, test_patterns, params) % Classify using a backpropagation network with a batch learning algorithm and co
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m backpropagation_sm.m

function [test_targets, Wh, Wo, J] = Backpropagation_SM(train_patterns, train_targets, test_patterns, params) % Classify using a backpropagation network with stochastic learning algorithm with mome
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html index.html

Learning Swing by Example: Examples (The Java™ Tutorials > Creating a GUI with JFC/Swing &g
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html summary.html

Summary (The Java™ Tutorials > Creating a GUI with JFC/Swing > Learning Swing by Example
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html answers-learn.html

Answers: Learning Swing by Example (The Java™ Tutorials > Creating a GUI with JFC/Swing >
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m buildkdaqr.m

% Build the KDA+QR solution (give a data structure) function [dataKDAQR, centroids, K]=buildKDAQR(L,S) % build the KDA+QR data, % with L learning vectors, and S an vector of the class sizes. %
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m svmlspex03.m

%SVMLSPex03.m %(Discrib the Object Function With Matrix Style) %Two Dimension SVM Problem, Two Class and Separable Situation % %Method from Thorsten Joachims: %"Making Large-Scale SVM Learning Pr