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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

Data exploration in ML Studio


Now, it's time to apply these concepts and start with data exploration and visualization using ML Studio. You will use some of the sample datasets, which comes by default, and do some basic exploration.

Visualizing an automobile price dataset

The Automobile price data (Raw) module is available on the left-hand side modules palette under Saved Datasets. This dataset is about automobiles distinguished by their make and model, including the price and features, such as the number of cylinders and MPG and an insurance risk score known to actuaries as symboling. If symboling has a value of +3, this indicates that the auto is risky and a value of -3 indicates that it is probably pretty safe.

Expand the Saved Datasets section in the modules palette. Drag the Automobile price data (Raw) module to the canvas. To get the visualized graph of the data, follow the steps:

  1. Right-click on the output port.

  2. Click on Visualize.

The visualization window will be displayed as a popup:

You...

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