java.lang.Object
- java.lang.Thread
- - gov.nih.mipav.model.algorithms.AlgorithmBase
  - - gov.nih.mipav.model.algorithms.LIBSVM

All Implemented Interfaces:

java.awt.event.ActionListener, java.awt.event.WindowListener, java.lang.Runnable, java.util.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) 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
java.lang.Thread.State, java.lang.Thread.UncaughtExceptionHandler

Field Summary

Fields
Modifier and Type	Field	Description
`private int`	`cross_validation`
`private java.lang.String`	`error_msg`
`private double[]`	`feature_max`
`private double[]`	`feature_min`
`private java.lang.String`	`input_file_name`
`(package private) java.lang.String[]`	`kernel_type_table`
`int`	`LIBSVM_VERSION`
`private java.lang.String`	`line`
`private double`	`lower`
`private int`	`max_index`
`private LIBSVM.svm_model`	`model`
`private java.lang.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`
`java.util.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) java.lang.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

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`private double`	`atof(java.lang.String s)`
`private int`	`atoi(java.lang.String s)`
`private void`	`do_cross_validation()`
`(package private) double`	`dot(LIBSVM.svm_node[] x, LIBSVM.svm_node[] y)`
`(package private) void`	`info(java.lang.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(java.lang.String[] argv, boolean haveFile)`
`private double`	`powi(double base, int times)`
`private void`	`predict(java.io.BufferedReader input, java.io.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(java.io.BufferedReader fp, LIBSVM.svm_model model)`
`private void`	`read_problem()`
`private void`	`read_XY(double[][] Xin, double[] y)`
`private java.lang.String`	`readline(java.io.BufferedReader fp)`
`private java.io.BufferedReader`	`rewind(java.io.BufferedReader fp, java.lang.String filename)`
`void`	`run_svm_predict(java.lang.String[] argv)`
`void`	`run_svm_scale(java.lang.String[] argv)`
`void`	`run_svm_toy(java.lang.String[] args)`
`LIBSVM.svm_model`	`run_svm_train(double[][] Xin, double[] y, java.lang.String[] argv)`
`void`	`run_svm_train(java.lang.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)`
`java.lang.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(java.io.BufferedReader fp)`
`LIBSVM.svm_model`	`svm_load_model(java.lang.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(java.lang.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, join, join, join, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, start, stop, suspend, toString, yield

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

LIBSVM_VERSION
```
public final int LIBSVM_VERSION
```
See Also:

Constant Field Values

rand
```
public final java.util.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 java.lang.String[] svm_type_table

kernel_type_table

final java.lang.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 java.lang.String input_file_name

model_file_name

private java.lang.String model_file_name

error_msg
```
private java.lang.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 java.lang.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 Detail
- LIBSVM
```
public LIBSVM()
```

Method Detail

info
```
void info(java.lang.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(java.lang.String model_file_name,
                           LIBSVM.svm_model model)
                    throws java.io.IOException

Throws:: java.io.IOException

read_model_header

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

svm_load_model

public LIBSVM.svm_model svm_load_model(java.lang.String model_file_name)
                                throws java.io.IOException

Throws:: java.io.IOException

svm_load_model

public LIBSVM.svm_model svm_load_model(java.io.BufferedReader fp)
                                throws java.io.IOException

Throws:: java.io.IOException

svm_check_parameter

public java.lang.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,
                                      java.lang.String[] argv)
                               throws java.io.IOException

Throws:: java.io.IOException

run_svm_train

public void run_svm_train(java.lang.String[] argv)
                   throws java.io.IOException

Throws:: java.io.IOException

atof

private double atof(java.lang.String s)

atoi

private int atoi(java.lang.String s)

parse_command_line

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

read_XY

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

read_problem

private void read_problem()
                   throws java.io.IOException

Throws:: java.io.IOException

predict

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

Throws:: java.io.IOException

predict_exit_with_help
```
private void predict_exit_with_help()
```

run_svm_predict

public void run_svm_predict(java.lang.String[] argv)
                     throws java.io.IOException

Throws:: java.io.IOException

scale_exit_with_help
```
private void scale_exit_with_help()
```

rewind

private java.io.BufferedReader rewind(java.io.BufferedReader fp,
                                      java.lang.String filename)
                               throws java.io.IOException

Throws:: java.io.IOException

output_target

private void output_target(double value)

output

private void output(int index,
                    double value)

readline

private java.lang.String readline(java.io.BufferedReader fp)
                           throws java.io.IOException

Throws:: java.io.IOException

run_svm_scale

public void run_svm_scale(java.lang.String[] argv)
                   throws java.io.IOException

Throws:: java.io.IOException

run_svm_toy

public void run_svm_toy(java.lang.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

Class LIBSVM

Nested Class Summary

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

Field Summary

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

Fields inherited from class java.lang.Thread

Constructor Summary

Method Summary

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

Methods inherited from class java.lang.Thread

Methods inherited from class java.lang.Object

Field Detail

LIBSVM_VERSION

rand

svm_print_stdout

svm_print_string

svm_type_table

kernel_type_table

param

prob

model

input_file_name

model_file_name

error_msg

cross_validation

nr_fold

svm_print_null

line

lower

upper

y_lower

y_upper

y_scaling

feature_max

feature_min

y_max

y_min

max_index

num_nonzeros

new_num_nonzeros

Constructor Detail

LIBSVM

Method Detail

info

solve_c_svc

solve_nu_svc

solve_one_class

solve_epsilon_svr

solve_nu_svr

svm_train_one

sigmoid_train

sigmoid_predict

multiclass_probability

svm_binary_svc_probability

predict_one_class_probability

svm_one_class_probability

svm_svr_probability

svm_group_classes

svm_train

svm_cross_validation

svm_get_svm_type

svm_get_nr_class

svm_get_labels

svm_get_sv_indices

svm_get_nr_sv

svm_get_svr_probability

powi

dot

k_function

svm_predict_values

svm_predict

svm_predict_probability

svm_save_model

read_model_header

svm_load_model

svm_load_model

svm_check_parameter

svm_check_probability_model

svm_set_print_string_function

train_exit_with_help