代码搜索：Labeled
找到约 414 项符合「Labeled」的源代码
代码结果 414
www.eeworm.com/read/273525/4208236
ado yxview_iarrow_draw.ado
*! version 1.0.0 22oct2002
// ---------------------------------------------------------------------------
// Drawing program for the ilabels type of yxview.
// WIP, just draws labeled points
www.eeworm.com/read/367152/9780153
m lda.m
% lda - Linear Discriminant Analysis (batch)
%
% [pldata,pvar,paxis] = lda(ldata[,options])
%
% _____OUTPUTS____________________________________________________________
% pldata projected labeled dat
www.eeworm.com/read/390081/8486728
doc
lt_expr le_expr gt_expr
ge_expr eq_expr ne_expr
unordered_expr ordered_expr unlt_expr
unle_expr ungt_expr unge_expr
uneq_expr fix_trunc_expr fix_ceil_expr
fix_floor_expr fix_round_expr
www.eeworm.com/read/303435/3811347
lib radiobuttons.xmcwp.lib
RADIOBUTTONS - convenience functions creating and using radio buttons
XtcwpCreateStringRadioButtons create an XmFrame containing radio
buttons labeled with strings
Function Prototypes:
Widge
www.eeworm.com/read/367152/9779889
m tallyc.m
% tallyc - Tally and sort classes
%
% [gdata,gindex,necl,cinfo]= tallyc(ldata[,cinfo])
%
% _____OUTPUT_____________________________________________________________
% gdata class sorted labeled data
www.eeworm.com/read/431675/8661691
m chernoffm.m
%CHERNOFFM Optimal discrimination mapping using Chernoff criterion
%
% W = cernoffm(A,n)
%
% Finds a mapping of the labeled dataset A to a n-dimensional
% linear subspace such that it maximizes
www.eeworm.com/read/431675/8662136
m fisherm.m
%FISHERM Optimal discrimination mapping (Fisher mapping)
%
% W = fisherm(A,n)
%
% Finds a mapping of the labeled dataset A to a n-dimensional
% linear subspace such that it maximizes the the bet
www.eeworm.com/read/418695/10935164
m chernoffm.m
%CHERNOFFM Optimal discrimination mapping using Chernoff criterion
%
% W = cernoffm(A,n)
%
% Finds a mapping of the labeled dataset A to a n-dimensional
% linear subspace such that it maximizes
www.eeworm.com/read/418695/10935459
m fisherm.m
%FISHERM Optimal discrimination mapping (Fisher mapping)
%
% W = fisherm(A,n)
%
% Finds a mapping of the labeled dataset A to a n-dimensional
% linear subspace such that it maximizes the the bet
www.eeworm.com/read/397102/8067980
m chernoffm.m
%CHERNOFFM Optimal discrimination mapping using Chernoff criterion
%
% W = cernoffm(A,n)
%
% Finds a mapping of the labeled dataset A to a n-dimensional
% linear subspace such that it maximizes