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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.
Upgraded with the latest SnapLogic Platform release.
4.26
main11181
Stable
Upgraded with the latest SnapLogic Platform release.
4.25
main9554
Stable
Upgraded with the latest SnapLogic Platform release.
4.24
main8556
Stable
Upgraded with the latest SnapLogic Platform release.
4.23
main7430
Stable
Upgraded with the latest SnapLogic Platform release.
4.22
main6403
Stable
Upgraded with the latest SnapLogic Platform release.
4.21
snapsmrc542
Stable
Upgraded with the latest SnapLogic Platform release.
4.20 Patch
mlcore8770
Stable
Adds the log4j dependency to the ML Core Snaps to resolve the "Could not initialize class org.apache.log4j.LogManager" error.
4.20
snapsmrc535
Stable
Upgraded with the latest SnapLogic Platform release.
4.19
snapsmrc528
Stable
Upgraded with the latest SnapLogic Platform release.
4.18
snapsmrc523
Stable
Upgraded with the latest SnapLogic Platform release.
4.17 Patch
ALL7402
Latest
Pushed automatic rebuild of the latest version of each Snap Pack to SnapLogic UAT and Elastic servers.
4.17
snapsmrc515
Latest
New Snap: Introducing the Clustering Snap thatperforms exploratory data analysis to find hidden patterns or groupings in data.
Enhanced the AutoML Snap. You can now:
Select algorithms to derive the top models.
Input the best model generated by another AutoML Snap from a previous execution.
View an interactive HTML report that contains statistics of up to 10 models.
Added the Snap Execution field to all Standard-mode Snaps. In some Snaps, this field replaces the existing Execute during preview check box.
4.16
snapsmrc508
Stable
New Snap: Introducing the AutoML Snap, which lets you automate the process of selecting machine learning algorithms and tuning hyperparameters. This Snap gives the best predictive model within the specified time limit.
4.15
snapsmrc500
Stable
New Snap Pack. Perform data modeling operations such as model training, cross-validation, and model-based predictions. Additionally, you can also execute Python scripts remotely. Snaps in this Snap Pack are:
Cross Validator -- Classification
Cross Validator -- Regression
Predictor -- Classification
Predictor -- Regression
Remote Python Script
Trainer -- Classification
Trainer -- Regression
Releases the Remote Python Executor account and the Remote Python Executor Dynamic account for the Remote Python Script Snap.