代码搜索：classification

找到约 3,679 项符合「classification」的源代码

代码结果 3,679
热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/415313/11076981

m svm_classify.m

function status = svm_classify(options, data, model, predictions) % SVM_CLASSIFY - Interface to SVM light, classification module % % STATUS = SVM_CLASSIFY(OPTIONS, DATA, MODEL, PREDICTIONS) % C
·
www.eeworm.com/read/413912/11137616

m svm_classify.m

function status = svm_classify(options, data, model, predictions) % SVM_CLASSIFY - Interface to SVM light, classification module % % STATUS = SVM_CLASSIFY(OPTIONS, DATA, MODEL, PREDICTIONS) % C
·
www.eeworm.com/read/248950/12531334

m demsvm2.m

function demsvm2() % DEMSVM2 - Demonstrate advanced Support Vector Machine features % % DEMSVM2 demonstrates the classification of a simple artificial data % set by a Support Vector Machine class
·
www.eeworm.com/read/248950/12534103

m svm_classify.m

function status = svm_classify(options, data, model, predictions) % SVM_CLASSIFY - Interface to SVM light, classification module % % STATUS = SVM_CLASSIFY(OPTIONS, DATA, MODEL, PREDICTIONS) % C
·
www.eeworm.com/read/204766/15333836

m demsvm2.m

function demsvm2() % DEMSVM2 - Demonstrate advanced Support Vector Machine features % % DEMSVM2 demonstrates the classification of a simple artificial data % set by a Support Vector Machine class
·
www.eeworm.com/read/111603/15509324

m fwd.m

function y = fwd(net,x) % FWD % % Compute the output of a support vector classification network. % % y = fwd(net, x); % % where x is a matrix of input patterns, where each column represent
·
www.eeworm.com/read/107559/15604936

m im_class_mle.m

function class=im_class_MLE(im,plot); % function class=im_class_MLE(im,plot); % % routine for performing classification of multispectral images using % Maximum Likelihood Estimation algorithm %
·
www.eeworm.com/read/189194/8485873

cla irisrul.cla

classification 8 4 0 w trapezoid 4.300000 4.300000 4.330000 5.830000 x trapezoid 2.300000 2.300000 2.342000 4.442000 y trapezoid 1.000000 1.000000 1.018000 1.918000 z trapezoid 0.100000 0.100000 0.110
·
www.eeworm.com/read/289487/8548547

m exlarsignalclassif.m

% Example of wavelet discriminant basis signal classification % % % 20/12/2005 clear all close all nbtrain=100; noise=1; nf=128; localisation=100:105; saut=1; name={'HeaviSine' 'D
·
www.eeworm.com/read/286662/8751919

m cart.m

function test_targets = CART(train_patterns, train_targets, test_patterns, params) % Classify using classification and regression trees % Inputs: % training_patterns - Train patterns % traini
·