MACHINE LEARNING. SUPERVISED LEARNING WITH IBM SPSS MODELER

By F. Marques

The goal of supervised machine learning is to build a model that makes evidence-based predictions in the presence of uncertainty. A supervised learning algorithm takes a known set of input data and known responses to the data (output) and trains a model to generate reasonable predictions for the response to new data. Supervised learning uses classification and regression techniques to develop predictive models. In this book, supervised learning Machine Learning techniques are developed and illustrated with full examples solved using the appropriate software. The IBM SPSS Modeler platform will be used, which is ideal for working with visual tools in all facets of Machine Learning.

• Format: Paperback
• Language: English
• ISBN: B0BGQJW57M
• ISBN13: 9798355226954
• Release Date: January 1
• Publisher: Independently Published
• Length: 242 Pages
• Weight: 1.07 lbs.
• Dimensions: 0.5" x 8.0" x 10.0"