magpie.attributes.selectors

Class RemoveDuplicateAttributeSelector

java.lang.Object

magpie.attributes.selectors.BaseAttributeSelector

magpie.attributes.selectors.RemoveDuplicateAttributeSelector

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Commandable, Options, Printable

public class RemoveDuplicateAttributeSelector
extends BaseAttributeSelector

Select only attributes that have unique values. Finds attributes that have the same value for each entry, and selects one of those two attributes.

Usage: [-tolerance <tol>]
tol: Tolerance of declaring two variables equivalent. Default = 1e-12

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected double	Tolerance Maximum absolute difference at which to declare two floats equal

Fields inherited from class magpie.attributes.selectors.BaseAttributeSelector

trained

Constructor Summary

Constructors

Constructor and Description
RemoveDuplicateAttributeSelector()

Method Summary

Modifier and Type	Method and Description
java.lang.String	printDescription(boolean htmlFormat) Print full name of object, and a simple description of the options.
java.lang.String	printUsage() Print out required format for options.
void	setOptions(java.util.List<java.lang.Object> Options) Set any options for this object.
void	setTolerance(double tol) Define the maximum difference at which two numbers are considered equal.
protected java.util.List<java.lang.Integer>	train_protected(Dataset data) Operation that actually does the work for training.

Methods inherited from class magpie.attributes.selectors.BaseAttributeSelector

about, applyAttributeSelection, clone, getSelectionNames, getSelections, isTrained, printCommand, printSelections, run, runCommand, train

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

Tolerance

protected double Tolerance

Maximum absolute difference at which to declare two floats equal

Constructor Detail

RemoveDuplicateAttributeSelector

public RemoveDuplicateAttributeSelector()

Method Detail

setOptions

public void setOptions(java.util.List<java.lang.Object> Options)
                throws java.lang.Exception

Description copied from interface: Options

Set any options for this object. If parsing the options fails, return an Exception with the usage as its message.

Parameters:

Options - Array of options as Objects - can be null

Throws:

java.lang.Exception - if problem with inputs

printUsage

public java.lang.String printUsage()

Description copied from interface: Options

Print out required format for options. For consistency, should start with "Usage: ".

Returns:

Usage for this function

setTolerance

public void setTolerance(double tol)

Define the maximum difference at which two numbers are considered equal.

Parameters:

tol - Desired tolerance (Default = 1e-6)

printDescription

public java.lang.String printDescription(boolean htmlFormat)

Description copied from interface: Printable

Print full name of object, and a simple description of the options. This description should print enough information to reproduce how this object was created, but not necessarily enough to run it (e.g., coefficients for the model).

Example: For a model training a separate WekaRegression for intermetallics

magpie.models.regression.SplitRegression

Splitter: AllMetalsSplitter
All Metals: magpie.models.regression.WekaRegression trees.REPTree
Contains Nonmetal: magpie.regression.LASSORegreession -maxterms 2

Specified by:

printDescription in interface Printable

Overrides:

printDescription in class BaseAttributeSelector

Parameters:

htmlFormat - Whether format for output to an HTML page (e.g., <div> to create indentation) or for printing to screen.

Returns:

String describing the model

See Also:

#printModel()

train_protected

protected java.util.List<java.lang.Integer> train_protected(Dataset data)

Description copied from class: BaseAttributeSelector

Operation that actually does the work for training. Must generate a list of attribute IDs

Specified by:

train_protected in class BaseAttributeSelector

Parameters:

data - Dataset used to train selector

Returns:

List of indexes of selected attributes