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Parse Numbers
(RapidMiner Studio Core)
Synopsis
This operator changes the type of selected nominal attributes to a numeric type. It also maps all values of these attributes to numeric values by parsing the numbers if possible.Description
The Parse Numbers operator is used for changing the type of nominal attributes to a numeric type. This operator not only changes the type of selected attributes but it also maps all values of these attributes to numeric values by parsing the numbers if possible. In contrast to the Nominal to Numerical operator, this operator directly parses numbers from the afore wrongly encoded as nominal values. The Nominal to Numeric operator is used when the values are actually nominal but you want to change them to numerical values. On the other hand the Parse Numbers operator is used when the values should actually be numerical but they are wrongly stored as nominal values. Please note that this operator will first check the stored nominal mappings for all attributes. If (old) mappings are still stored which actually are nominal (without the corresponding data being part of the ExampleSet), the attribute will not be converted. Please use the Guess Types operator in these cases.
Differentiation
Nominal to Numerical
The Nominal to Numerical operator provides various coding types to convert nominal attributes to numerical attributes. On the other hand the Parse Numbers operator is used when the values should actually be numerical but they are wrongly stored as nominal values.
Input
example set input (Data Table)
This input port expects an ExampleSet. It is the output of the Subprocess operator in the attached Example Process. The output of other operators can also be used as input. The ExampleSet should have at least one nominal attribute because if there is no such attribute, the use of this operator does not make sense.
Output
example set output (Data Table)
The ExampleSet with selected nominal attributes converted to numeric types is output of this port.
original (Data Table)
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
- attribute_filter_typeThis parameter allows you to select the attribute selection filter; the method you want to use for selecting the required 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. (Since RapidMiner 6.0.4 the Operator will fail if a selected Attribute is not in the ExampleSet)
- subset: This option allows selection of multiple attributes through a list. All attributes of the ExampleSet are present in the list; required attributes can be easily selected. This option will not work if the meta data is not known. When this option is selected another parameter becomes visible in the Parameters panel. (Since RapidMiner 6.0.4 the Operator will fail if a selected Attribute is not in the ExampleSet)
- 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 numeric type. Users should have a 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. 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.
- attributeThe desired attribute can be selected from this option. The attribute name can be selected from the drop down box of attribute parameter if the meta data is known. Range: string
- attributesThe 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 on which the conversion from nominal to numeric will take place; all other attributes will remain unchanged. Range: string
- regular_expressionThe attributes whose name matches this expression will be selected. Regular expression is a very powerful tool but needs a detailed explanation to beginners. It is always good to specify the regular expression through the edit and preview regular expression menu. This menu gives a good idea of regular expressions. This menu also allows you to try different expressions and preview the results simultaneously. This will enhance your concept of regular expressions. Range: string
- use_except_expressionIf enabled, an exception to the selected type can be specified. When this option is selected another parameter (except value type) becomes visible in the Parameters panel. Range: boolean
- except_regular_expressionThis option allows you to specify a regular expression. Attributes matching this expression will be filtered out even if they match the first expression (expression that was specified in the regular expression parameter). Range: string
- value_typeThe type of attributes to be selected can be chosen from a drop down list. One of the following types can be chosen: nominal, text, binominal, polynominal, file_path. Range: selection
- use_value_type_exception If enabled, an exception to the selected type can be specified. When this option is selected another parameter (except value type) becomes visible in the Parameters panel. Range: boolean
- except_value_typeThe attributes matching this type will be removed from the final output even if they matched the previously mentioned type i.e. value type parameter's value. One of the following types can be selected here: nominal, text, binominal, polynominal, file_path. Range: selection
- block_typeThe block type of attributes to be selected can be chosen from a drop down list. The only possible value here is 'single_value' Range: selection
- use_block_type_exception If enabled, an exception to the selected block type can be specified. When this option is selected another parameter (except block type) becomes visible in the Parameters panel. Range: boolean
- except_block_typeThe attributes matching this block type will be removed from the final output even if they matched the previously mentioned block type. Range: selection
- numeric_conditionThe numeric condition for testing examples of numeric attributes is specified here. For example the numeric condition '> 6' will keep all nominal attributes and all numeric attributes having a value of greater than 6 in every example. A combination of conditions is possible: '> 6 && < 11' or '<= 5 || < 0'. But && and || cannot be used together in one numeric condition. Conditions like '(> 0 && < 2) || (>10 && < 12)' are not allowed because they use both && and ||. Use a blank space after '>', '=' and '<' e.g. '<5' will not work, so use '< 5' instead. Range: string
- include_special_attributesThe special attributes are attributes with special roles which identify the examples. In contrast regular attributes simply describe the examples. Special attributes are: id, label, prediction, cluster, weight and batch. Range: boolean
- invert_selectionIf this parameter is set to true, it acts as a NOT gate, it reverses the selection. In that case all the selected attributes are unselected and previously unselected attributes are selected. For example if attribute 'att1' is selected and attribute 'att2' is unselected prior to checking of this parameter. After checking of this parameter 'att1' will be unselected and 'att2' will be selected. Range: boolean
- decimal_characterThis character is used as the decimal character. Range: char
- grouped_digitsThis option decides whether grouped digits should be parsed or not. If this option is set to true, grouping character parameter should be specified. Range: boolean
- grouping_characterThis character is used as the grouping character. If this character is found between numbers, the numbers are combined and this character is ignored. For example if "22-14" is present in the nominal attribute and "-" is set as grouping character, then "2214" will be stored in the corresponding numerical attribute. Range: char
- infinity_stringThis parameter can be set to parse a specific infinity representation (e.g. "Infinity"). If it is not set, the local specific infinity representation will be used. Range: string
- unparsable_value_handlingThis selects the method for handling occurrences of values which are not parsable to numbers. The unparsable value can either be skipped, treated as an error or replaced with a missing value. Range: selection
Tutorial Processes
Nominal to Numeric conversion by the Parse Numbers operator
This Example Process starts with a Subprocess operator. The Subprocess operator provides an ExampleSet as its output. The ExampleSet has some nominal attributes. But these nominal attributes actually wrongly store numerical values as nominal values. A breakpoint is inserted here so that you can have a look at the ExampleSet. The type of these attributes should be numerical. To convert these nominal attributes to numerical attributes the Parse Numbers operator is applied. All parameters are used with default values. The resultant ExampleSet can be seen in the Results Workspace. You can see that the type of all attributes has been changed from nominal to numerical type.