Machine Learning Module

The Spectrum™ Technology Platform Machine Learning Module provides the ability to fit supervised and unsupervised machine learning 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.

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.

Logistic Regression

Logistic Regression creates models from datasets that use binary 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 in K-Means Clustering, Logistic Regression, and Java Model Scoring.