TD_​POWERTRANSFORM

At its core, this function takes a logical-runtime series - time series or numerically sequenced series - as an input and applies a power transform to the series, producing another series (1D array) as an output. The passed in logical input series can be either a univariate or multivariate series, in which case the function respectively produces a univariate or multivariate output series. The data scientist has a choice of preserving the input series indexing mechanism, or even altering it, via the OUTPUT_FMT(INDEX_STYLE()) declaration.

Options

B

Germane for log functions. The log to be applied. Collectively, P and B determine the power function to be applied

BACK_TRANSFORM

Flag set to 0 or 1. BACK_TRANSFORM(0) is the default - means the forward transform is to be applied. BACK_TRANSFORM(1) means the back transform is to be applied.

LAMBDA

Germane for the Box-Cox transformation

OutputFormat

Specifies the INDEX_STYLE of the output format.

P

Incoming magnitudes are raised to this power. Collectively, P and B determine the power function to be applied

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 Configuration7 ×
• Python Script2 ×
• Boolean Configuration1 ×
• Component Input1 ×
• Component Output1 ×
• Show all 12 nodes

Extensions

• FeatureKNIME Base nodes
• FeatureKNIME Database
• FeatureKNIME Quick Forms

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