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Table of Contents
maxLevel3

Overview

This is a Transform type Snap that enables you to predict the target field for an unlabeled document. An unlabeled document is one that does not have a label field. So, the Snap reads this unlabeled document and predicts the label field. Predictions are made based on the regression model built by the Trainer (Regression) Snap.

Input and Output

Expected input: An unlabeled document and the regression model for predicting the target field. 

Expected output: Predictions from the regression model based on the input document. 

Expected upstream Snaps:

  • First input view: Any Snap that generates an unlabeled document document is usable as an upstream Snap. For example, JSON Parser, JSON Generator, CSV Parser, CSV Generator, Mapper, and so on.
  • Second input view: Any Snap that reads and outputs the regression model. For example, a combination of File Reader, and JSON Parser.

Expected downstream Snaps: CSV/JSON Formatter Snap and File Writer Snap can be used to write the output to file.

Prerequisites

The input document must be in tabular format (no nested structure). 

Configuring Accounts

Accounts are not used with this Snap.

Configuring Views

Input

This Snap has exactly two document input views. The first input view is for the unlabeled document that requires prediction. The second input view is for the regression model to be used for the prediction.
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. Modify this to be more specific, especially if there are more than one of the same Snap in the pipeline.



Example

The following use case demonstrates a real-world scenario for using this Snap:



Snap History


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ML Core Snap Pack
ML Core Snap Pack
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