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Microsoft Azure Machine Learning

You're reading from  Microsoft Azure Machine Learning

Product type Book
Published in Jun 2015
Publisher
ISBN-13 9781784390792
Pages 212 pages
Edition 1st Edition
Languages
Authors (2):
Sumit Mund Sumit Mund
Profile icon Sumit Mund
Christina Storm Christina Storm
Profile icon Christina Storm
View More author details

Table of Contents (21) Chapters

Microsoft Azure Machine Learning
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Introduction ML Studio Inside Out Data Exploration and Visualization Getting Data in and out of ML Studio Data Preparation Regression Models Classification Models Clustering A Recommender System Extensibility with R and Python Publishing a Model as a Web Service Case Study Exercise I Case Study Exercise II Index

Training, scoring, and evaluating modules


As with regression problems, which you saw in the previous chapter, with classification problems, you can start with an algorithm and train it with data. You can then score ideally with the test data and evaluate the performance of the model.

Navigate to the Train | Score | Evaluate option on the screen.

The Train, Score, and Evaluate modules are the same as you used for regression. The Train module requires the name of the target (class) variable. The Evaluate module generates evaluation metrics for classification.

If you want to tune parameters of an algorithm by parameter sweeping, you can use the same Sweep Parameters module.

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