TD_​ARIMAVALIDATE

The TD_ARIMAVALIDATE function first performs an “In-Sample” forecast, followed by an analysis of the produced residuals. The aim of this analysis is to provide the data scientist with a collection of metrics which are useful for model selection and expose the produced residuals, such that a number of model validation statistical tests can be conducted.

Options

FIT_METRICS

Flag indicating whether or not to generate the secondary result set that contains the model metadata statistics. A value of FIT_METRICS(1) means generate the secondary result set. A value of FIT_METRICS(0) means do not generate the secondary result set. Default is FIT_METRICS(0). The generated result set can be retrieved by issuing a TD_EXTRACT_RESULTS against the analytical result table containing the results.

OutputFormat

Specifies the INDEX_STYLE of the output format.

RESIDUALS

Flag indicating whether or not to generate the tertiary result set that contains the model residuals. A value of RESIDUALS(1) means generate the tertiary result set. A value of RESIDUALS(0) means do not generate the tertiary result set. Default is RESIDUALS(0). The generated result set can be retrieved by issuing a TD_EXTRACT_RESULTS against the analytical result table containing the results.

Output Schema

Output Schema, if Volatile is true then use user login as the schema.

Output Table

Output Table

VAL Location

VAL Location

Volatile

Specifies whether the table should be a VOLATILE table. If true, then the table is automatically deleted, otherwise it is users responsibility to remove or clean it up for space.

Nodes

• String Configuration3 ×
• Integer Configuration2 ×
• Python Script2 ×
• Boolean Configuration1 ×
• Component Input1 ×
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Extensions

• FeatureKNIME Base nodes
• FeatureKNIME Database
• FeatureKNIME Quick Forms

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