Lag (Time Series)

Parameters

• individual_lags

  The lag attributes can be selected by the drop down menu if the meta data is known. For each attribute an integer lag value has to be specified. If overwrite attributes is not selected, the same attribute can be lagged more than one time with different lag values.

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• individual_attribute

  The lag attribute can be selected by the drop down menu if the meta data is known. It can also be typed in manually.

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• lag

  This parameter defines the number of lags for the individual attribute. Example i will contain the value of Example i-lag. The first lag values will be filled with missing values. lag value can be positive or negative.

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• add_default_lag

  If this parameter is selected a default lag for a set of attributes can be specified. The set of these default lagged attributes can be selected by the attribute filter. The default lag value for is given by the parameter default lag.

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• attribute_filter_type

  This parameter allows you to select the filter for the default lag attributes selection filter; the method you want to select the attributes on which the default lag is applied. The different filter types are:

  • all: This option selects all attributes of the ExampleSet. This is the default option.
  • single: This option allows the selection of a single attribute. The required attribute is selected by the attribute parameter.
  • subset: This option allows the selection of multiple attributes through a list (see parameter attributes). If the meta data of the ExampleSet is known all attributes are present in the list and the required ones can easily be selected.
  • regular_expression: This option allows you to specify a regular expression for the attribute selection. The regular expression filter is configured by the parameters regular expression, use except expression and except expression.
  • 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. The value type filter is configured by the parameters value type, use value type exception, except value type.
  • block_type: This option allows the 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. The block type filter is configured by the parameters block type, use block type exception, except block type.
  • no_missing_values: This option selects all attributes of the ExampleSet as attributes which do not contain a missing value in any example. Attributes that have even a single missing value are not selected.
  • numeric_value_filter: All numeric attributes whose examples all match a given numeric condition are selected. The condition is specified by the numeric condition parameter.
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• attribute

  The required attribute can be selected from this option. The attribute name can be selected from the drop down box of the parameter if the meta data is known.

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• 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. They can be shifted to the right list, which is the list of selected time series attributes.

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• regular_expression

  Attributes whose names match this expression will be selected. The expression can be specified through the edit and preview regular expression menu. This menu gives a good idea of regular expressions and it also allows you to try different expressions and preview the results simultaneously.

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• use_except_expression

  If enabled, an exception to the first regular expression can be specified. This exception is specified by the except regular expression parameter.

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• except_regular_expression

  This 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 regular expression parameter).

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• value_type

  This option allows to select a type of attribute.

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• use_value_type_exception

  If enabled, an exception to the selected type can be specified. This exception is specified by the except value type parameter.

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• except_value_type

  The attributes matching this type will be removed from the final output even if they matched the before selected type, specified by the value type parameter.

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• block_type

  This option allows to select a block type of attribute.

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• use_block_type_exception

  If enabled, an exception to the selected block type can be specified. This exception is specified by the except block type parameter.

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• except_block_type

  The attributes matching this block type will be removed from the final output even if they matched the before selected type by the block type parameter.

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• numeric_condition

  The numeric condition used by the numeric condition filter type. A numeric attribute is selected if all examples match the specified condition for this attribute. For example the numeric condition '> 6' will keep 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 ||.

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• invert_selection

  If this parameter is set to true the selection is reversed. In that case all attributes not matching the specified condition are selected. Special attributes are not selected independent of the invert selection parameter as along as the include special attributes parameter is not set to true. If so the condition is also applied to the special attributes and the selection is reversed if this parameter is checked.

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• include_special_attributes

  Special attributes are attributes with special roles. These are: id, label, prediction, cluster, weight and batch. Also custom roles can be assigned to attributes. By default special attributes are not selected irrespective of the filter conditions. If this parameter is set to true, special attributes are also tested against conditions specified and those attributes are selected that match the conditions.

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• default_lag

  This parameter defines the default lag for the attributes selected by the attribute filter. All selected attributes will be lagged with this default lag value. Example i will contain the value of Example i-lag. The first lag values will be filled with missing values. lag value can be positive or negative.

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• overwrite_attributes

  This parameter indicates if the original time series attributes are overwritten by the lagged time series. If this parameter is set to false, the lagged time series are added as new attributes to the ExampleSet. The name of these new attributes will be <attribute-name> - <lag> or *<attribute-name> + <lag>* if the lag is negative.

  Note that selecting this parameter can increase runtime (it required copying the input ExampleSet to ensure that there are no data leaks).

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• extend_exampleset

  This parameter indicates if the ExampleSet should be extended by n Examples (where n is the maximum lag specified). Attributes that are not selected for lagging are filled with missing values.

  Note that selecting this parameter can increase runtime (it required copying the input ExampleSet to ensure that there are no data leaks).

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