代码搜索：Labeled

找到约 414 项符合「Labeled」的源代码

代码结果 414
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www.eeworm.com/read/360995/10069843

m istarget.m

%ISTARGET true if the label is target % % I = ISTARGET(A) % % Returns true for the objects from dataset A which are labeled % 'target'. % % I = ISTARGET(LABA) % % It also works when no da
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www.eeworm.com/read/358191/10194624

out image.out

Enter image size The input image is 0010000 0011000 0000100 0001100 1000100 1110000 1110000 The labeled image is 0020000 0022000 0000300 0003300 4000300 4440000 4440000
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www.eeworm.com/read/161587/10395043

out image.out

Enter image size The input image is 0010000 0011000 0000100 0001100 1000100 1110000 1110000 The labeled image is 0020000 0022000 0000300 0003300 4000300 4440000 4440000
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www.eeworm.com/read/299984/7139933

m cnormc.m

%CNORMC Classifier normalisation for ML posterior probabilities % % W = CNORMC(W,A) % % INPUT % W Classifier mapping % A Labeled dataset % % OUTPUT % W Scaled classifier mapping % % DESCRIPT
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www.eeworm.com/read/460435/7250408

m cnormc.m

%CNORMC Classifier normalisation for ML posterior probabilities % % W = CNORMC(W,A) % % INPUT % W Classifier mapping % A Labeled dataset % % OUTPUT % W Scaled classifier mapping % % DESCRIPT
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www.eeworm.com/read/459616/7270638

out image.out

Enter image size The input image is 0010000 0011000 0000100 0001100 1000100 1110000 1110000 The labeled image is 0020000 0022000 0000300 0003300 4000300 4440000 4440000
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www.eeworm.com/read/451547/7461871

m istarget.m

%ISTARGET true if the label is target % % I = ISTARGET(A) % % Returns true for the objects from dataset A which are labeled % 'target'. % % I = ISTARGET(LABA) % % It also works when no da
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www.eeworm.com/read/450608/7480074

m cnormc.m

%CNORMC Classifier normalisation for ML posterior probabilities % % W = CNORMC(W,A) % % INPUT % W Classifier mapping % A Labeled dataset % % OUTPUT % W Scaled classifier mapping % % DESCRIPT
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www.eeworm.com/read/441245/7672610

m cnormc.m

%CNORMC Classifier normalisation for ML posterior probabilities % % W = CNORMC(W,A) % % INPUT % W Classifier mapping % A Labeled dataset % % OUTPUT % W Scaled classifier mapping % % DESCRIPT
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www.eeworm.com/read/137160/13341792

m cnormc.m

%CNORMC Classifier normalisation for ML posterior probabilities % % W = CNORMC(W,A) % % INPUT % W Classifier mapping % A Labeled dataset % % OUTPUT % W Scaled classifier mapping % % DESCRIPT
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