Package gov.nih.mipav.model.algorithms

Class LIBSVM

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.LIBSVM

All Implemented Interfaces:

ActionListener, WindowListener, Runnable, EventListener

public class LIBSVM
extends AlgorithmBase

Copyright (c) 2000-2023 Chih-Chung Chang and Chih-Jen Lin All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither name of copyright holders nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model selection tool for C-SVM classification. This document explains the use of libsvm. Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2:27:1--27:27, 2011. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm LIBSVM implementation document is available at http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
(package private) class	LIBSVM.Cache
(package private) class	LIBSVM.decision_function
(package private) class	LIBSVM.Kernel
(package private) class	LIBSVM.ONE_CLASS_Q
(package private) class	LIBSVM.QMatrix
(package private) class	LIBSVM.Solver
(package private) final class	LIBSVM.Solver_NU
(package private) class	LIBSVM.SVC_Q
class	LIBSVM.svm_model
class	LIBSVM.svm_node
class	LIBSVM.svm_parameter
static interface	LIBSVM.svm_print_interface
class	LIBSVM.svm_problem
(package private) class	LIBSVM.svm_toy_frame
(package private) class	LIBSVM.SVR_Q

Nested classes/interfaces inherited from class java.lang.Thread

Thread.Builder, Thread.State, Thread.UncaughtExceptionHandler

Field Summary

Fields

Modifier and Type	Field	Description
private int	cross_validation
private String	error_msg
private double[]	feature_max
private double[]	feature_min
private String	input_file_name
(package private) final String[]	kernel_type_table
final int	LIBSVM_VERSION
private String	line
private double	lower
private int	max_index
private LIBSVM.svm_model	model
private String	model_file_name
private long	new_num_nonzeros
private int	nr_fold
private long	num_nonzeros
private LIBSVM.svm_parameter	param
private LIBSVM.svm_problem	prob
final Random	rand
private LIBSVM.svm_print_interface	svm_print_null
private LIBSVM.svm_print_interface	svm_print_stdout
private LIBSVM.svm_print_interface	svm_print_string
(package private) final String[]	svm_type_table
private double	upper
private double	y_lower
private double	y_max
private double	y_min
private boolean	y_scaling
private double	y_upper

Fields inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

destFlag, destImage, image25D, mask, maxProgressValue, minProgressValue, multiThreadingEnabled, nthreads, progress, progressModulus, progressStep, runningInSeparateThread, separable, srcImage, threadStopped

Fields inherited from class java.lang.Thread

MAX_PRIORITY, MIN_PRIORITY, NORM_PRIORITY

Constructor Summary

Constructors

Constructor	Description
LIBSVM()

Method Summary

Modifier and Type	Method	Description
private double	atof(String s)
private int	atoi(String s)
private void	do_cross_validation()
(package private) double	dot(LIBSVM.svm_node[] x, LIBSVM.svm_node[] y)
(package private) void	info(String s)
(package private) double	k_function(LIBSVM.svm_node[] x, LIBSVM.svm_node[] y, LIBSVM.svm_parameter param)
private void	multiclass_probability(int k, double[][] r, double[] p)
private void	output(int index, double value)
private void	output_target(double value)
private void	parse_command_line(String[] argv, boolean haveFile)
private double	powi(double base, int times)
private void	predict(BufferedReader input, DataOutputStream output, LIBSVM.svm_model model, int predict_probability)
private void	predict_exit_with_help()
private double	predict_one_class_probability(LIBSVM.svm_model model, double dec_value)
private boolean	read_model_header(BufferedReader fp, LIBSVM.svm_model model)
private void	read_problem()
private void	read_XY(double[][] Xin, double[] y)
private String	readline(BufferedReader fp)
private BufferedReader	rewind(BufferedReader fp, String filename)
void	run_svm_predict(String[] argv)
void	run_svm_scale(String[] argv)
void	run_svm_toy(String[] args)
LIBSVM.svm_model	run_svm_train(double[][] Xin, double[] y, String[] argv)
void	run_svm_train(String[] argv)
void	runAlgorithm()	Actually runs the algorithm.
private void	scale_exit_with_help()
private double	sigmoid_predict(double decision_value, double A, double B)
private void	sigmoid_train(int l, double[] dec_values, double[] labels, double[] probAB)
private void	solve_c_svc(LIBSVM.svm_problem prob, LIBSVM.svm_parameter param, double[] alpha, LIBSVM.Solver.SolutionInfo si, double Cp, double Cn)
private void	solve_epsilon_svr(LIBSVM.svm_problem prob, LIBSVM.svm_parameter param, double[] alpha, LIBSVM.Solver.SolutionInfo si)
private void	solve_nu_svc(LIBSVM.svm_problem prob, LIBSVM.svm_parameter param, double[] alpha, LIBSVM.Solver.SolutionInfo si)
private void	solve_nu_svr(LIBSVM.svm_problem prob, LIBSVM.svm_parameter param, double[] alpha, LIBSVM.Solver.SolutionInfo si)
private void	solve_one_class(LIBSVM.svm_problem prob, LIBSVM.svm_parameter param, double[] alpha, LIBSVM.Solver.SolutionInfo si)
private void	svm_binary_svc_probability(LIBSVM.svm_problem prob, LIBSVM.svm_parameter param, double Cp, double Cn, double[] probAB)
String	svm_check_parameter(LIBSVM.svm_problem prob, LIBSVM.svm_parameter param)
int	svm_check_probability_model(LIBSVM.svm_model model)
void	svm_cross_validation(LIBSVM.svm_problem prob, LIBSVM.svm_parameter param, int nr_fold, double[] target)
void	svm_get_labels(LIBSVM.svm_model model, int[] label)
int	svm_get_nr_class(LIBSVM.svm_model model)
int	svm_get_nr_sv(LIBSVM.svm_model model)
void	svm_get_sv_indices(LIBSVM.svm_model model, int[] indices)
int	svm_get_svm_type(LIBSVM.svm_model model)
double	svm_get_svr_probability(LIBSVM.svm_model model)
private void	svm_group_classes(LIBSVM.svm_problem prob, int[] nr_class_ret, int[][] label_ret, int[][] start_ret, int[][] count_ret, int[] perm)
LIBSVM.svm_model	svm_load_model(BufferedReader fp)
LIBSVM.svm_model	svm_load_model(String model_file_name)
private int	svm_one_class_probability(LIBSVM.svm_problem prob, LIBSVM.svm_model model, double[] prob_density_marks)
double	svm_predict(LIBSVM.svm_model model, LIBSVM.svm_node[] x)
double	svm_predict_probability(LIBSVM.svm_model model, LIBSVM.svm_node[] x, double[] prob_estimates)
double	svm_predict_values(LIBSVM.svm_model model, LIBSVM.svm_node[] x, double[] dec_values)
void	svm_save_model(String model_file_name, LIBSVM.svm_model model)
void	svm_set_print_string_function(LIBSVM.svm_print_interface print_func)
private double	svm_svr_probability(LIBSVM.svm_problem prob, LIBSVM.svm_parameter param)
LIBSVM.svm_model	svm_train(LIBSVM.svm_problem prob, LIBSVM.svm_parameter param)
(package private) LIBSVM.decision_function	svm_train_one(LIBSVM.svm_problem prob, LIBSVM.svm_parameter param, double Cp, double Cn)
private void	train_exit_with_help()

Methods inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

actionPerformed, addListener, addProgressChangeListener, calculateImageSize, calculatePrincipleAxis, computeElapsedTime, computeElapsedTime, convertIntoFloat, delinkProgressToAlgorithm, delinkProgressToAlgorithmMulti, displayError, errorCleanUp, finalize, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, generateProgressValues, getDestImage, getElapsedTime, getMask, getMaxProgressValue, getMinProgressValue, getNumberOfThreads, getProgress, getProgressChangeListener, getProgressChangeListeners, getProgressModulus, getProgressStep, getProgressValues, getSrcImage, isCompleted, isImage25D, isMultiThreadingEnabled, isRunningInSeparateThread, isThreadStopped, linkProgressToAlgorithm, linkProgressToAlgorithm, makeProgress, notifyListeners, removeListener, removeProgressChangeListener, run, setCompleted, setImage25D, setMask, setMaxProgressValue, setMinProgressValue, setMultiThreadingEnabled, setNumberOfThreads, setProgress, setProgressModulus, setProgressStep, setProgressValues, setProgressValues, setRunningInSeparateThread, setSrcImage, setStartTime, setThreadStopped, startMethod, windowActivated, windowClosed, windowClosing, windowDeactivated, windowDeiconified, windowIconified, windowOpened

Methods inherited from class java.lang.Thread

activeCount, checkAccess, clone, countStackFrames, currentThread, dumpStack, enumerate, getAllStackTraces, getContextClassLoader, getDefaultUncaughtExceptionHandler, getId, getName, getPriority, getStackTrace, getState, getThreadGroup, getUncaughtExceptionHandler, holdsLock, interrupt, interrupted, isAlive, isDaemon, isInterrupted, isVirtual, join, join, join, join, ofPlatform, ofVirtual, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, sleep, start, startVirtualThread, stop, suspend, threadId, toString, yield

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Details

LIBSVM_VERSION

public final int LIBSVM_VERSION

See Also:

• Constant Field Values

rand

public final Random rand

svm_print_stdout

private LIBSVM.svm_print_interface svm_print_stdout

svm_print_string

private LIBSVM.svm_print_interface svm_print_string

svm_type_table

final String[] svm_type_table

kernel_type_table

final String[] kernel_type_table

param

private LIBSVM.svm_parameter param

prob

private LIBSVM.svm_problem prob

model

private LIBSVM.svm_model model

input_file_name

private String input_file_name

model_file_name

private String model_file_name

error_msg

private String error_msg

cross_validation

private int cross_validation

nr_fold

private int nr_fold

svm_print_null

private LIBSVM.svm_print_interface svm_print_null

line

private String line

lower

private double lower

upper

private double upper

y_lower

private double y_lower

y_upper

private double y_upper

y_scaling

private boolean y_scaling

feature_max

private double[] feature_max

feature_min

private double[] feature_min

y_max

private double y_max

y_min

private double y_min

max_index

private int max_index

num_nonzeros

private long num_nonzeros

new_num_nonzeros

private long new_num_nonzeros

Constructor Details

LIBSVM

public LIBSVM()

Method Details

info

void info(String s)

solve_c_svc

private void solve_c_svc(LIBSVM.svm_problem prob,
 LIBSVM.svm_parameter param,
 double[] alpha,
 LIBSVM.Solver.SolutionInfo si,
 double Cp,
 double Cn)

solve_nu_svc

private void solve_nu_svc(LIBSVM.svm_problem prob,
 LIBSVM.svm_parameter param,
 double[] alpha,
 LIBSVM.Solver.SolutionInfo si)

solve_one_class

private void solve_one_class(LIBSVM.svm_problem prob,
 LIBSVM.svm_parameter param,
 double[] alpha,
 LIBSVM.Solver.SolutionInfo si)

solve_epsilon_svr

private void solve_epsilon_svr(LIBSVM.svm_problem prob,
 LIBSVM.svm_parameter param,
 double[] alpha,
 LIBSVM.Solver.SolutionInfo si)

solve_nu_svr

private void solve_nu_svr(LIBSVM.svm_problem prob,
 LIBSVM.svm_parameter param,
 double[] alpha,
 LIBSVM.Solver.SolutionInfo si)

svm_train_one

LIBSVM.decision_function svm_train_one(LIBSVM.svm_problem prob,
 LIBSVM.svm_parameter param,
 double Cp,
 double Cn)

sigmoid_train

private void sigmoid_train(int l,
 double[] dec_values,
 double[] labels,
 double[] probAB)

sigmoid_predict

private double sigmoid_predict(double decision_value,
 double A,
 double B)

multiclass_probability

private void multiclass_probability(int k,
 double[][] r,
 double[] p)

svm_binary_svc_probability

private void svm_binary_svc_probability(LIBSVM.svm_problem prob,
 LIBSVM.svm_parameter param,
 double Cp,
 double Cn,
 double[] probAB)

predict_one_class_probability

private double predict_one_class_probability(LIBSVM.svm_model model,
 double dec_value)

svm_one_class_probability

private int svm_one_class_probability(LIBSVM.svm_problem prob,
 LIBSVM.svm_model model,
 double[] prob_density_marks)

svm_svr_probability

private double svm_svr_probability(LIBSVM.svm_problem prob,
 LIBSVM.svm_parameter param)

svm_group_classes

private void svm_group_classes(LIBSVM.svm_problem prob,
 int[] nr_class_ret,
 int[][] label_ret,
 int[][] start_ret,
 int[][] count_ret,
 int[] perm)

svm_train

public LIBSVM.svm_model svm_train(LIBSVM.svm_problem prob,
 LIBSVM.svm_parameter param)

svm_cross_validation

public void svm_cross_validation(LIBSVM.svm_problem prob,
 LIBSVM.svm_parameter param,
 int nr_fold,
 double[] target)

svm_get_svm_type

public int svm_get_svm_type(LIBSVM.svm_model model)

svm_get_nr_class

public int svm_get_nr_class(LIBSVM.svm_model model)

svm_get_labels

public void svm_get_labels(LIBSVM.svm_model model,
 int[] label)

svm_get_sv_indices

public void svm_get_sv_indices(LIBSVM.svm_model model,
 int[] indices)

svm_get_nr_sv

public int svm_get_nr_sv(LIBSVM.svm_model model)

svm_get_svr_probability

public double svm_get_svr_probability(LIBSVM.svm_model model)

powi

private double powi(double base,
 int times)

dot

double dot(LIBSVM.svm_node[] x,
 LIBSVM.svm_node[] y)

k_function

double k_function(LIBSVM.svm_node[] x,
 LIBSVM.svm_node[] y,
 LIBSVM.svm_parameter param)

svm_predict_values

public double svm_predict_values(LIBSVM.svm_model model,
 LIBSVM.svm_node[] x,
 double[] dec_values)

svm_predict

public double svm_predict(LIBSVM.svm_model model,
 LIBSVM.svm_node[] x)

svm_predict_probability

public double svm_predict_probability(LIBSVM.svm_model model,
 LIBSVM.svm_node[] x,
 double[] prob_estimates)

svm_save_model

public void svm_save_model(String model_file_name,
 LIBSVM.svm_model model)
                    throws IOException

Throws:

IOException

read_model_header

private boolean read_model_header(BufferedReader fp,
 LIBSVM.svm_model model)

svm_load_model

public LIBSVM.svm_model svm_load_model(String model_file_name)
                                throws IOException

Throws:

IOException

svm_load_model

public LIBSVM.svm_model svm_load_model(BufferedReader fp)
                                throws IOException

Throws:

IOException

svm_check_parameter

public String svm_check_parameter(LIBSVM.svm_problem prob,
 LIBSVM.svm_parameter param)

svm_check_probability_model

public int svm_check_probability_model(LIBSVM.svm_model model)

svm_set_print_string_function

public void svm_set_print_string_function(LIBSVM.svm_print_interface print_func)

train_exit_with_help

private void train_exit_with_help()

do_cross_validation

private void do_cross_validation()

run_svm_train

public LIBSVM.svm_model run_svm_train(double[][] Xin,
 double[] y,
 String[] argv)
                               throws IOException

Throws:

IOException

run_svm_train

public void run_svm_train(String[] argv)
                   throws IOException

Throws:

IOException

atof

private double atof(String s)

atoi

private int atoi(String s)

parse_command_line

private void parse_command_line(String[] argv,
 boolean haveFile)

read_XY

private void read_XY(double[][] Xin,
 double[] y)

read_problem

private void read_problem()
                   throws IOException

Throws:

IOException

predict

private void predict(BufferedReader input,
 DataOutputStream output,
 LIBSVM.svm_model model,
 int predict_probability)
              throws IOException

Throws:

IOException

predict_exit_with_help

private void predict_exit_with_help()

run_svm_predict

public void run_svm_predict(String[] argv)
                     throws IOException

Throws:

IOException

scale_exit_with_help

private void scale_exit_with_help()

rewind

private BufferedReader rewind(BufferedReader fp,
 String filename)
                       throws IOException

Throws:

IOException

output_target

private void output_target(double value)

output

private void output(int index,
 double value)

readline

private String readline(BufferedReader fp)
                 throws IOException

Throws:

IOException

run_svm_scale

public void run_svm_scale(String[] argv)
                   throws IOException

Throws:

IOException

run_svm_toy

public void run_svm_toy(String[] args)

runAlgorithm

public void runAlgorithm()

Description copied from class: AlgorithmBase

Actually runs the algorithm. Implemented by inheriting algorithms.

Specified by:

runAlgorithm in class AlgorithmBase