代码搜索：Operating
找到约 10,000 项符合「Operating」的源代码
代码结果 10,000
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/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/428451/8867273
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/427586/8932092
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/183445/9158724
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/374698/9388905
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/360895/10072688
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/162027/10344117
c os.c
/**
* @file os.c
*
* Operating system functions used by uCIP.
*
* System specific stuff for ISS/OS running on the ls808.
*/
#include
#include
#include
#includ
www.eeworm.com/read/161189/10439918
m fund.m
%
% Computes forward model predictions for the EM-38 problem.
%
function f=fund(sigma)
global DATA;
%
% Number of layers.
%
M=11;
%
% Layer thicknesses.
%
D=0.2*ones(10,1);
%
% Operating frequency.
%
www.eeworm.com/read/278889/10490625
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