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Predictive Analytics using Rattle and Qlik Sense

Predictive Analytics using Rattle and Qlik Sense

By : Ferran Garcia Pagans
4 (5)
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Predictive Analytics using Rattle and Qlik Sense

Predictive Analytics using Rattle and Qlik Sense

4 (5)
By: Ferran Garcia Pagans

Overview of this book

If you are a business analyst who wants to understand how to improve your data analysis and how to apply predictive analytics, then this book is ideal for you. This book assumes you have some basic knowledge of statistics and a spreadsheet editor such as Excel, but knowledge of QlikView is not required.
Table of Contents (11 chapters)
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10
Index

Regression performance


To measure the performance of a regression, the distance between the predicted outputs and the actual outputs, is a good model performance measure.

Rattle offers us a good way to see predicted values versus the actual value—the Predicted versus Observed plot. To test this plot, you need to create a regression model. You can download a sample dataset from the UCI Machine Learning Repository (http://archive.ics.uci.edu/ml; Irvine, CA: University of California, School of Information and Computer Science), or from Kaggle (http://www.kaggle.com/). On some websites, such as the UCI Machine Learning Repository, the datasets are classified by the task you want to perform with the dataset.

Predicted versus Observed Plot

Imagine we have to create a model to predict the price of a house. Click on the Evaluate tab:

Rattle's Evaluate tab offers us two good options for a regression model as shown in the preceding screenshot:

  • Predicted versus Observed Plot: We will use this option to...

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