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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
Toc

Table of Contents (21) Chapters close

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

Linear regression


Linear regression is one of the regression algorithms available in ML Studio. It tries to fit a line to the dataset. It is a popular algorithm and probably the oldest regression algorithm. We will use it to train the model to make prediction for one of the sample datasets available: automobile price data (Raw). This dataset is about automobiles distinguished by their make and model and other features. It also includes price. More information on the dataset can be found at https://archive.ics.uci.edu/ml/datasets/Automobile.

We will use price as a label or the target variable here. So, given the automobile features, you need to predict the price of the automobile.

Go to ML Studio and create a new experiment. Then, expand Saved Datasets in the modules palette to the left of the screen. Drag the Automobile price data (Raw) module to the canvas.

Then, expand Data Transformation and then Sample and Split in the modules palette and drag the Split module to the canvas. Set the Fraction...

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