Weight by Deviation

Synopsis

This operator calculates the relevance of attributes of the given ExampleSet based on the (normalized) standard deviation of the attributes.

Description

The Weight by Deviation operator calculates the weight of attributes with respect to the label attribute based on the (normalized) standard deviation of the attributes. The higher the weight of an attribute, the more relevant it is considered. The standard deviations can be normalized by average, minimum, or maximum of the attribute. Please note that this operator can be only applied on ExampleSets with numerical label.

Standard deviation shows how much variation or dispersion exists from the average (mean, or expected value). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data points are spread out over a large range of values. The standard deviation is a measure of how spread out numbers are. The formula is simple: it is the square root of the Variance.

Input

example set

This input port expects an ExampleSet. It is output of the Retrieve operator in the attached Example Process.

Output

weights

This port delivers the weights of the attributes with respect to the label attribute. The attributes with higher weight are considered more relevant.

example set

The ExampleSet that was given as input is passed without changing to the output through this port. This is usually used to reuse the same ExampleSet in further operators or to view the ExampleSet in the Results Workspace.

Parameters

Normalize weights

This parameter indicates if the calculated weights should be normalized or not. If set to true, all weights are normalized in the range from 0 to 1.

Sort weights

This parameter indicates if the attributes should be sorted according to their weights in the results. If this parameter is set to true, the order of the sorting is specified using the排序方向parameter.

Sort direction

This parameter is only available when thesort weightsparameter is set to true. This parameter specifies the sorting order of the attributes according to their weights.

Normalize

This parameter indicates if the standard deviation should be divided by the minimum, maximum, or average of the attribute.