Package

weka.classifiers.meta

Synopsis

Performs a grid search of parameter pairs for the a classifier (Y-axis, default is LinearRegression with the "Ridge" parameter) and the PLSFilter (X-axis, "# of Components") and chooses the best pair found for the actual predicting.

The initial grid is worked on with 2-fold CV to determine the values of the parameter pairs for the selected type of evaluation (e.g., accuracy). The best point in the grid is then taken and a 10-fold CV is performed with the adjacent parameter pairs. If a better pair is found, then this will act as new center and another 10-fold CV will be performed (kind of hill-climbing). This process is repeated until no better pair is found or the best pair is on the border of the grid.
In case the best pair is on the border, one can let GridSearch automatically extend the grid and continue the search. Check out the properties 'gridIsExtendable' (option '-extend-grid') and 'maxGridExtensions' (option '-max-grid-extensions <num>').

GridSearch can handle doubles, integers (values are just cast to int) and booleans (0 is false, otherwise true). float, char and long are supported as well.

The best filter/classifier setup can be accessed after the buildClassifier call via the getBestFilter/getBestClassifier methods.
Note on the implementation: after the data has been passed through the filter, a default NumericCleaner filter is applied to the data in order to avoid numbers that are getting too small and might produce NaNs in other schemes.

Available in Weka 3.6.x - 3.7.1. Available via the package management system for Weka >= 3.7.2 (gridSearch).

Options

The table below describes the options available for GridSearch.

Option	Description
XBase	The base of X.
XExpression	The expression for the X value (parameters: BASE, FROM, TO, STEP, I).
XMax	The maximum of X.
XMin	The minimum of X.
XProperty	The X property to test (normally the filter).
XStep	The step size of X.
YBase	The base of Y.
YExpression	The expression for the Y value (parameters: BASE, FROM, TO, STEP, I).
YMax	The maximum of Y.
YMin	The minimum of Y (normally the classifier).
YProperty	The Y property to test (normally the classifier).
YStep	The step size of Y.
classifier	The base classifier to be used.
debug	If set to true, classifier may output additional info to the console.
evaluation	Sets the criterion for evaluating the classifier performance and choosing the best one.
filter	The filter to be used (only used for setup).
gridIsExtendable	Whether the grid can be extended.
logFile	The log file to log the messages to.
maxGridExtensions	The maximum number of grid extensions, -1 for unlimited.
sampleSizePercent	The sample size (in percent) to use in the initial grid search.
seed	The random number seed to be used.
traversal	Sets type of traversal of the grid, either by rows or columns.

Capabilities

The table below describes the capabilites of GridSearch.

Capability	Supported
Class	Date class, Numeric class
Attributes	Missing values, Numeric attributes, Date attributes
Min # of instances	1