Discretize by Binning
Synopsis
This operator discretizes the selected numerical attributes into user-specified number of bins. Bins of equal range are automatically generated, the number of the values in different bins may vary.
Description
This operator discretizes the selected numerical attributes to nominal attributes. The number of bins parameter is used to specify the required number of bins. This discretization is performed by simple binning. The range of numerical values is partitioned into segments of equal size. Each segment represents a bin. Numerical values are assigned to the bin representing the segment covering the numerical value. Each range is named automatically. The naming format for range can be changed using the range name type parameter. Values falling in the range of a bin are named according to the name of that range. This operator also allows you to apply binning only on a range of values. This can be enabled by using the define boundaries parameter. The min value and max value parameter are used for defining the boundaries of the range. If there are any values that are less than the min value parameter, a separate range is created for them. Similarly if there are any values that are greater than the max value parameter, a separate range is created for them. Then, the discretization by binning is performed only on the values that are within the specified boundaries.
Differentiation
Discretize by Frequency
The Discretize by Frequency operator creates bins in such a way that the number of unique values in all bins are (almost) equal.
Discretize by Size
The Discretize by Size operator creates bins in such a way that each bin has user-specified size (i.e. number of examples).
Discretize by Entropy
The discretization is performed by selecting bin boundaries such that the entropy is minimized in the induced partitions.
Discretize by User Specification
This operator discretizes the selected numerical attributes into user-specified classes.
Input
example set input
This input port expects an ExampleSet. It is output of the Retrieve (Deprecated) operator in the attached Example Process. the output of other operators can also be used as input. It is essential that meta data should be attached with the data for the input because attributes are specified in their meta data. The Retrieve (Deprecated) operator provides meta data along-with the data. Note that there should be at least one numerical attribute in the input ExampleSet, otherwise the use of this operator does not make sense.
Output
example set output
The selected numerical attributes are converted into nominal attributes by binning and the resultant ExampleSet is delivered through this port.
original
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.
preprocessing model
This port delivers the preprocessing model, which has information regarding the parameters of this operator in the current process.
Parameters
attribute filter type
This parameter allows you to select the attribute selection filter; the method you want to use for selecting attributes. It has the following options:
- all: This option simply selects all the attributes of the ExampleSet. This is the default option.
- single: This option allows selection of a single attribute. When this option is selected another parameter (attribute) becomes visible in the Parameters panel.
- subset: This option allows selection of multiple attributes through a list. All attributes of ExampleSet are present in the list; required attributes can be easily selected. This option will not work if meta data is not known. When this option is selected another parameter becomes visible in the Parameters panel.
- regular_expression: This option allows you to specify a regular expression for attribute selection. When this option is selected some other parameters (regular expression, use except expression) become visible in the Parameters panel.
- value_type: This option allows selection of all the attributes of a particular type. It should be noted that types are hierarchical. For example real and integer types both belong to the numeric type. Users should have basic understanding of type hierarchy when selecting attributes through this option. When this option is selected some other parameters (value type, use value type exception) become visible in the Parameters panel.
- block_type: This option is similar in working to the value_type option. This option allows selection of all the attributes of a particular block type. It should be noted that block types may be hierarchical. For example value_series_start and value_series_end block types both belong to the value_series block type. When this option is selected some other parameters (block type, use block type exception) become visible in the Parameters panel.
- no_missing_values: This option simply selects all the attributes of the ExampleSet which don't contain a missing value in any example. Attributes that have even a single missing value are removed.
- numeric_value_filter: When this option is selected another parameter (numeric condition) becomes visible in the Parameters panel. All numeric attributes whose examples all satisfy the mentioned numeric condition are selected. Please note that all nominal attributes are also selected irrespective of the given numerical condition.
attribute
The required attribute can be selected from this option. The attribute name can be selected from the drop down box of the parameter attribute if the meta data is known.
attributes
The required attributes can be selected from this option. This opens a new window with two lists. All attributes are present in the left list and can be shifted to the right list, which is the list of selected attributes.