Vector Assembler

Merges multiple columns into a vector column.

Input

It takes in a DataFrame and transforms it to another DataFrame

Output

It adds a new column to the incoming DataFrame. The new column contains the values of the input columns concatenated into a vector in the specified order.

Type

ml-transformer

Class

fire.nodes.ml.NodeVectorAssembler

Fields

Name	Title	Description
inputCols	Input Columns	Input column of type - all numeric, boolean and vector
outputCol	Output Column	Output column name
handleInvalid	Handle Invalid	How to handle invalid data (NULL values). Options are ‘skip’ (filter out rows with invalid data), ‘error’ (throw an error), or ‘keep’ (return relevant number of NaN in the output).

Examples

h2: VectorAssembler Node Example

Assume that we have a DataFrame with the columns id, hour, mobile, userFeatures, and clicked:

    id | hour | mobile | userFeatures     | clicked
   ----|------|--------|------------------|---------
    0  | 18   | 1.0    | [0.0, 10.0, 0.5] | 1.0


If we set VectorAssembler's **input Selected columns** to hour, mobile, and userFeatures and **output column** to features, after transformation we should get the following DataFrame:

 id | hour | mobile | userFeatures     | clicked | features
----|------|--------|------------------|---------|-----------------------------
 0  | 18   | 1.0    | [0.0, 10.0, 0.5] | 1.0     | [18.0, 1.0, 0.0, 10.0, 0.5]