Parameters

java.lang.Object
- keel.Algorithms.Neural_Networks.gmdh.Parameters

Direct Known Subclasses:

SetupParameters
```
public class Parameters
extends java.lang.Object
```
Class Parameters

Since:

JDK1.5

Version:

0.1

Author:

Written by Nicolas Garcia Pedrajas (University of Cordoba) 27/02/2007

Field Summary

Fields
Modifier and Type	Field and Description
`double`	`alpha` Problem coefficients
`java.lang.String`	`bp_type` Not used
`boolean`	`cross_validation` Check if test,validation or cross validation data is going to be used
`int`	`cycles` Number of cycles
`double`	`eta` Problem coefficients
`double`	`improve` Problem coefficients
`double`	`lambda` Problem coefficients
`java.lang.String`	`model_output` File names
`int`	`n_test_patterns` Number of train, validation and test patterns
`int`	`n_train_patterns` Number of train, validation and test patterns
`int`	`n_val_patterns` Number of train, validation and test patterns
`int[]`	`Nhidden` Number of units in each layer
`int`	`Nhidden_layers` Number of hidden layers
`int`	`Ninputs` Number of units in each layer
`int`	`Noutputs` Number of units in each layer
`java.lang.String`	`problem` Type of the problem ( CLASSIFICATION \| REGRESSION )
`boolean`	`save` Save at the end of the output
`long`	`seed` Random seed
`boolean`	`test_data` Check if test,validation or cross validation data is going to be used
`java.lang.String`	`test_file` File names
`java.lang.String`	`test_output` File names
`double`	`threshold` Problem coefficients
`boolean`	`tipify_inputs` Check if is going to be tipified
`java.lang.String`	`train_file` File names
`java.lang.String`	`train_output` File names
`java.lang.String[]`	`transfer` Transfer function ( LOG \| HTAN \| LINEAR )
`boolean`	`val_data` Check if test,validation or cross validation data is going to be used
`java.lang.String`	`val_file` File names
`boolean`	`verbose` Verbose output

Constructor Summary

Constructors
Constructor and Description

Parameters()
Empty constructor

Constructors
Constructor and Description
`Parameters()` Empty constructor

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type Method and Description

void LoadParameters(java.lang.String file_name)
Load parameters from file_name to global
- Methods inherited from class java.lang.Object
  clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`LoadParameters(java.lang.String file_name)` Load parameters from file_name to global

- Field Detail
  - Nhidden
```
public int[] Nhidden
```
    Number of units in each layer
  - Noutputs
```
public int Noutputs
```
    Number of units in each layer
  - Ninputs
```
public int Ninputs
```
    Number of units in each layer
  - n_train_patterns
```
public int n_train_patterns
```
    Number of train, validation and test patterns
  - n_val_patterns
```
public int n_val_patterns
```
    Number of train, validation and test patterns
  - n_test_patterns
```
public int n_test_patterns
```
    Number of train, validation and test patterns
  - cycles
```
public int cycles
```
    Number of cycles
  - Nhidden_layers
```
public int Nhidden_layers
```
    Number of hidden layers
  - test_data
```
public boolean test_data
```
    Check if test,validation or cross validation data is going to be used
  - val_data
```
public boolean val_data
```
    Check if test,validation or cross validation data is going to be used
  - cross_validation
```
public boolean cross_validation
```
    Check if test,validation or cross validation data is going to be used
  - tipify_inputs
```
public boolean tipify_inputs
```
    Check if is going to be tipified
  - verbose
```
public boolean verbose
```
    Verbose output
  - save
```
public boolean save
```
    Save at the end of the output
  - eta
```
public double eta
```
    Problem coefficients
  - alpha
```
public double alpha
```
    Problem coefficients
  - lambda
```
public double lambda
```
    Problem coefficients
  - improve
```
public double improve
```
    Problem coefficients
  - threshold
```
public double threshold
```
    Problem coefficients
  - seed
```
public long seed
```
    Random seed
  - train_file
```
public java.lang.String train_file
```
    File names
  - test_file
```
public java.lang.String test_file
```
    File names
  - train_output
```
public java.lang.String train_output
```
    File names
  - test_output
```
public java.lang.String test_output
```
    File names
  - model_output
```
public java.lang.String model_output
```
    File names
  - val_file
```
public java.lang.String val_file
```
    File names
  - problem
```
public java.lang.String problem
```
    Type of the problem ( CLASSIFICATION | REGRESSION )
  - bp_type
```
public java.lang.String bp_type
```
    Not used
  - transfer
```
public java.lang.String[] transfer
```
    Transfer function ( LOG | HTAN | LINEAR )
- Constructor Detail
  - Parameters
```
public Parameters()
```
    Empty constructor
- Method Detail
  - LoadParameters
```
public void LoadParameters(java.lang.String file_name)
```
    Load parameters from file_name to global
    
    Parameters:
    
    file_name - Data file name

Class Parameters

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

Nhidden

Noutputs

Ninputs

n_train_patterns

n_val_patterns

n_test_patterns

cycles

Nhidden_layers

test_data

val_data

cross_validation

tipify_inputs

verbose

save

eta

alpha

lambda

improve

threshold

seed

train_file

test_file

train_output

test_output

model_output

val_file

problem

bp_type

transfer

Constructor Detail

Parameters

Method Detail

LoadParameters