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(This article was first published on <strong><a href="http://www.r-exercises.com/2017/08/24/big-data-analytics-with-revoscaler-exercises/"> R-exercises</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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In this set of exercise , you will explore how to handle bigdata with RevoscaleR package from Microsoft R (previously Revolution Analytics).It comes with Microsoft R client . You can get it from <a rel="nofollow" href="https://docs.microsoft.com/en-us/r-server/r-client/what-is-microsoft-r-client" target="_blank">here</a> . get the Credit card fraud data set from <a rel="nofollow" href="https://packages.revolutionanalytics.com/datasets/" target="_blank">revolutionanalytics</a> and lets get started<br>
Answers to the exercises are available <a rel="nofollow" href="http://www.r-exercises.com/2017/08/24/big-data-analytics-with-revoscaler-solutions/" target="_blank">here</a>.Please check the documentation before starting these exercise set </p>
<p>If you obtained a different (correct) answer than those listed on the solutions page, please feel free to post your answer as a comment on that page.</p>
<p><strong>Exercise 1</strong><br>
The heart of RevoScaleR is the xdf file format , convert the creditcardfraud data set into xdf format . </p>
<p><strong>Exercise 2</strong></p>
<p>use the newly created xdf file to get information about the variables and print 10 rows to check the data .</p>
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<aside><img src="http://www.r-exercises.com/2017/08/24/big-data-analytics-with-revoscaler-exercises/"></aside>
<div><strong>Learn more</strong> about importing big data in the online course <a rel="nofollow" href="http://www.r-exercises.com/product/data-mining-with-r-go-from-beginner-to-advanced/" target="_blank">Data Mining with R: Go from Beginner to Advanced</a>. In this course you will learn how to
<ul>
<li>work with different data import techniques,</li>
<li>know how to import data and transform it for a specific moddeling or analysis goal,</li>
<li>and much more.</li>
</ul>
</div>
</div>
<p><strong>Exercise 3</strong><br>
use rxSummary ,get the summary for variables gender, balance ,cardholder where numTrans is greater than 10 </p>
<p><strong>Exercise 4</strong><br>
use rxDataStep and create a variable avgbalpertran which is balance /numTran+numIntlTran .use rxGetInfo to check if your changes being reflected in the xdf data </p>
<p><strong>Exercise 5</strong><br>
use rxCor and find the correlation between the newly created variable and fraudRisk<br>
<strong>Exercise 6</strong><br>
use rxLinMod to construct the linear regression of fraudRisk on gender,balance and cardholder. Dont forget to check the summary of the model . </p>
<p><strong>Exercise 7</strong><br>
Find the contingency table of fraudRisk and Gender , use rxCrossTab .Hint : Figure out how to include factors in the formula . </p>
<p><strong>Exercise 8</strong><br>
use rxCube to find the mean balance for each of the two genders .</p>
<p><strong>Exercise 9</strong><br>
Create a histogram from the xdf file on balance to show the relative frequency histogram . </p>
<p><strong>Exercise 10</strong><br>
Create a two panel histogram with gender and fradurisk as explanatory variable to show the relative frequency of fraudrisk in two genders . </p>
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<h3>Related exercise sets:</h3>
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<li><a rel="nofollow" href="http://www.r-exercises.com/2015/10/09/vector-exercises/" title="Vector exercises" target="_blank">Vector exercises </a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/2016/05/12/cross-tabulation-with-xtabs-exercises/" title="Cross Tabulation with Xtabs exercises" target="_blank">Cross Tabulation with Xtabs exercises </a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/2016/04/20/data-exploration-with-tables-exercises/" title="Data Exploration with Tables exercises" target="_blank">Data Exploration with Tables exercises </a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/start-here-to-learn-r/" target="_blank">Explore all our (>1000) R exercises</a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/r-courses/" target="_blank">Find an R course using our R Course Finder</a> directory</li>
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