代码搜索：roc
找到约 663 项符合「roc」的源代码
代码结果 663
www.eeworm.com/read/432021/8638004
roc
#!/bin/csh
#
# $Id: roc.txt 1339 2006-09-21 19:46:28Z tbailey $
# $Log$
# Revision 1.2 2005/10/05 06:18:35 nadya
# use full path for "rm". Asssume everybody has /bin/rm.
#
# Revision 1.1.1.1 2005/0
www.eeworm.com/read/190459/8443096
m roc.m
function [AREA,SE,RESULT_S,FPR_ROC,TPR_ROC,TNa,TPa,FNa,FPa]=roc(RESULT,CLASS,fig)
% Receiver Operating Characteristic (ROC) curve of a binary classifier
%
% >> [area, se, deltab, oneMinusSpec, sen
www.eeworm.com/read/289334/8558645
m~ roc.m~
function [FP,FN]=roc(dfce,y)
% ROC Computes Receive Operator Characteristic.
%
% Synopsis:
% [FP,FN]=roc(dfce,y)
%
% Description:
% It computes false positive rate FP and false negative rate FN
%
www.eeworm.com/read/289334/8558652
m roc.m
function [FP,FN]=roc(dfce,y)
% ROC computes Receiver Operating Characteristic (ROC) curves.
%
% Synopsis:
% [FP,FN]=roc(dfce,y)
%
% Description:
% It computes false positive rate FP and false neg
www.eeworm.com/read/432021/8638046
txt roc.txt
#!/bin/csh
#
# $Id: roc.txt 1339 2006-09-21 19:46:28Z tbailey $
# $Log$
# Revision 1.2 2005/10/05 06:18:35 nadya
# use full path for "rm". Asssume everybody has /bin/rm.
#
# Revision 1.1.1.1 2005/0
www.eeworm.com/read/431675/8662087
m roc.m
%ROC Receiver-operator curve
%
% e = roc(D,k)
%
% Computes k points of the receiver-operator curve of the classifier
% W for the labeled data set D, which is typically the result of
% D = A*W*clas
www.eeworm.com/read/386874/8720368
sav roc.sav
www.eeworm.com/read/386050/8768184
m roc.m
%ROC Receiver-Operator Curve
%
% E = ROC(A,W,C,N)
% E = ROC(B,C,N)
%
% INPUT
% A Dataset
% W Trained classifier, or
% B Classification result, B = A*W*CLASSC
% C Index of desired clas
www.eeworm.com/read/429504/8804832
m roc.m
function [AREA,SE,RESULT_S,FPR_ROC,TPR_ROC,TNa,TPa,FNa,FPa]=roc(RESULT,CLASS,fig)
% Receiver Operating Characteristic (ROC) curve of a binary classifier
%
% >> [area, se, deltab, oneMinusSpec, sen
www.eeworm.com/read/384944/8827763
m roc.m
function [tp, fp] = roc(t, y)
%
% ROC - generate a receiver operating characteristic curve
%
% [TP,FP] = ROC(T,Y) gives the true-positive rate (TP) and false positive
% rate (FP), where Y is a c