代码搜索：validation

找到约 7,219 项符合「validation」的源代码

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www.eeworm.com/read/264420/11315436

m psplit.m

function [tx,ty,vx,vy]=pslit(x,y,p) % % Positional percentage split % % p defines the position to split the data % 0-p (%) = training % p-100 (%) = validation % [D L]=size(x); tsiz
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www.eeworm.com/read/400646/11570990

dr nummath.dr

Numerical Mathematical Library README Simple Introduction plus revision history Makefile Makefile for making the library Linear Algebra, Basic Operations LinAlg.h Declaration of Matrices, V
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www.eeworm.com/read/348119/11610432

m rjnn.m

function [k,mu,alpha,sigma,nabla,delta,ypred,ypredv,post] = rjnn(x,y,chainLength,Ndata,bFunction,par,xv,yv); % PURPOSE : Computes the parameters and number of parameters of a radial basis function (RB
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www.eeworm.com/read/346715/11728720

java wrappersubseteval.java

/* * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either vers
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www.eeworm.com/read/258574/11853582

dr nummath.dr

Numerical Mathematical Library README Simple Introduction plus revision history Makefile Makefile for making the library Linear Algebra, Basic Operations LinAlg.h Declaration of Matrices, V
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www.eeworm.com/read/256102/12028087

h time.h

// Fig. 9.8: Time.h // Declaration of class Time. // Member functions defined in Time.cpp. // prevent multiple inclusions of header file #ifndef TIME_H #define TIME_H // Time abstract data t
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www.eeworm.com/read/255755/12057976

m testp.m

%TESTP Error estimation of Parzen classifier % % E = TESTP(A,H,T) % E = TESTP(A,H) % % INPUT % A input dataset % H matrix smoothing parameters (optional, def: determined via %
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www.eeworm.com/read/150905/12249283

m testp.m

%TESTP Error estimation of Parzen classifier % % E = TESTP(A,H,T) % E = TESTP(A,H) % % INPUT % A input dataset % H matrix smoothing parameters (optional, def: determined via %
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www.eeworm.com/read/149739/12353572

m testp.m

%TESTP Error estimation of Parzen classifier % % E = TESTP(A,H,T) % E = TESTP(A,H) % % INPUT % A input dataset % H matrix smoothing parameters (optional, def: determined via %
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www.eeworm.com/read/130491/14189848

1 mailcross.1

\" t .TH MAILCROSS 1 "Bayesian Text Classification Tools" "Version 1.3" "" .SH NAME mailcross \- a cross-validation tester for use with dbacl. .SH SYNOPSIS .HP .B mailcross .I command [ .I command_a
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