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Overview

The Feature Synthesis Snap generates new features for a base or primary dataset by joining it with other datasets (reference datasets) linked together by common identifiers. Features are measurements of data points in a dataset. Using this Snap enables you to view statistical data of all related datasets in the base dataset itself. Categorical and numeric data will get different set of features. Some of the features generated are:

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Input

This Snap has at least two document input views.
OutputThis Snap has exactly one document output view.
ErrorThis Snap has at most one document error view.

Troubleshooting

None.

Limitations and Known Issues

None.

Modes

Snap Settings

LabelRequired. The name for the Snap. You can modify this to be specific, especially if you have more than one of the same Snap in your pipeline.
PolicySpecify the base and reference datasets and fields.
Base view

The input view to which the base dataset is connected.

Default value: input0 (name of the input view)

Base path

The field in the base dataset that is to be used as the base field. This has to be the common identifier for joining with the reference dataset.

Example: $customer_id

Default value: [None]

Ref view

View where the reference dataset is the input.

Default value: input0 (name of the input view)

Ref path

The field in the reference dataset that is to be used. This field must have the same values as in the base field.

Example: $customer_id

Default value: [None]


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  Snap Execution



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Specifies the execution type:

  • Validate & Execute: Performs limited execution of the Snap (up to 50 records) during Pipeline validation; performs full execution of the Snap (unlimited records) during Pipeline execution.
  • Execute only: Performs full execution of the Snap during Pipeline execution; does not execute the Snap during Pipeline validation.
  • Disabled: Disables the Snap and, by extension, its downstream Snaps.

Default value: Validate & Execute


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Expand
titleUnderstanding the Pipeline

The base dataset in this example is a collection of customer records. It has the following fields:

  • $customer_id
  • $firstname
  • $lastname
  • $create_time

The reference dataset is a collection of transactions made by the customers listed in the base dataset. It has the following fields:

  • $transaction_id
  • $customer_id
  • $source
  • $num_item
  • $total 

Both datasets are provided by the CSV Generator Snaps titled Customers and Transactions. These are passed through a Type Converter Snaps so that all data types are mapped correctly. This is required to enable the Feature Synthesis Snap to generate features accurately. 

A preview of the customer and transaction datasets that are output by the CSV Generator Snaps is as shown below:

 

The field $customer_id is common between both datasets. The Feature Synthesis Snap will use this field to join datasets and is configured as shown below:

 

The customer dataset is connected to the first input view (titled customer); so this view becomes the Base view. Similarly, the transaction dataset is connected to the second input view (titled transaction); so that becomes the Ref view.

Upon successful execution, the Feature Synthesis Snap generates features and adds them to the base dataset as shown below: 

The same output is shown in a JSON format to let you see the full list of features:

Download this Pipeline.

Downloads

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Attachments
patterns*.slp,*.zip
 

Additional Resources

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Glossary

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ML Data Preparation Snap Pack
ML Data Preparation Snap Pack
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