Machine Learning Module

The Spectrum™ Technology Platform Machine Learning Module provides the ability to bin numeric data, fit supervised and unsupervised machine learning models, and score data in those models.

Note: The Machine Learning Module is supported only on Windows and Linux operating systems.

Binning

Binning divides records into groups (bins) for a continuous variable without taking into account objective information. You can perform unsupervised binning in one of two ways: using equal-width bins or equal-frequency bins.

Binning Lookup

Binning Lookup applies previously defined binning to new data using existing bins created in dataflows using the Binning stage.

K-Means Clustering

K-Means Clustering creates models based on analytical clustering, which segments a set of records into clusters of similar records based on data values.

Linear Regression

Linear Regression creates models from datasets that use continuous objectives with input variables.

Logistic Regression

Logistic Regression creates models from datasets that use binary objectives with input variables.

Principal Component Analysis

Principal Component Analysis (PCA) is a statistical process that converts a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables known as principal components.

Random Forest Classification

Random Forest Classification creates models from datasets that use binary or multinomial objectives with input variables.

Random Forest Regression creates models from datasets that use continuous objectives with input variables.

Java Model Scoring

This feature scores new data using the formula created when you fit a machine learning model.

Machine Learning Model Management

Machine Learning Model Management enables you to manage all machine learning models on your Spectrum™ Technology Platform server. You can expose, unexpose, or delete models. Additionally, you can view detailed information for each model and compare any two models of the same type.

Note: The Machine Learning Module uses an underlying H2O.ai library for modeling algorithms and Java Model Scoring.