代码搜索：predict
找到约 2,271 项符合「predict」的源代码
代码结果 2,271
www.eeworm.com/read/338899/12274553
c svm-predict.c
#include
#include
#include
#include
#include "svm.h"
char* line;
int max_line_len = 1024;
struct svm_node *x;
int max_nr_attr = 64;
struct svm_model* model;
www.eeworm.com/read/251528/12339427
m kf_predict.m
%KF_PREDICT Perform Kalman Filter prediction step
%
% Syntax:
% [X,P] = KF_PREDICT(X,P,A,Q,B,U)
%
% In:
% X - Nx1 mean state estimate of previous step
% P - NxN state covariance of previ
www.eeworm.com/read/336977/12403629
obj svm-predict.obj
www.eeworm.com/read/336977/12403640
c svm-predict.c
#include
#include
#include
#include
#include "svm.h"
char* line;
int max_line_len = 1024;
struct svm_node *x;
int max_nr_attr = 64;
struct svm_model* model;
www.eeworm.com/read/336977/12403737
java svm_predict.java
import libsvm.*;
import java.io.*;
import java.util.*;
class svm_predict {
private static double atof(String s)
{
return Double.valueOf(s).doubleValue();
}
private static int atoi(String s)
{
www.eeworm.com/read/148789/12425857
rd predict.ksvm.rd
\name{predict.ksvm}
\alias{predict.ksvm}
\alias{predict,ksvm-method}
\title{predict method for support vector object}
\description{Prediction of test data using support vector machines}
\usage{
\S
www.eeworm.com/read/131588/14136146
m predict_performance.m
function a = predict_performance(algorithm, algorithm_params, features, targets, region)
% Predict the final performance of an algorithm from the learning curves
% Inputs:
% algorithm
www.eeworm.com/read/130548/14187213
c svm-predict.c
#include
#include
#include
#include
#include "svm.h"
char* line;
int max_line_len = 1024;
struct svm_node *x;
int max_nr_attr = 64;
struct svm_model* model;
www.eeworm.com/read/130548/14187241
java svm_predict.java
import libsvm.*;
import java.io.*;
import java.util.*;
class svm_predict {
private static double atof(String s)
{
return Double.valueOf(s).doubleValue();
}
private static int atoi(String s)
{
www.eeworm.com/read/129915/14217593
m predict_performance.m
function a = predict_performance(algorithm, algorithm_params, features, targets, region)
% Predict the final performance of an algorithm from the learning curves
% Inputs:
% algorithm