scikit-feature: Open-Source Feature Selection Repository in Python

scikit-feature is an open-source feature selection repository in python, with around 40 popular algorithms in feature selection research. It is developed by Data Mining and Machine Learning Lab at Arizona State University.

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R: Remove constant and identical features programmatically

##### Removing constant features cat("n## Removing the constants features.n") for (f in names(train)) { if (length(unique(train[[f]])) == 1) { cat(f, "is constant in train. We delete it.n") train[[f]] <- NULL t...

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Compare The Performance of Machine Learning Algorithms in R

How do you compare the estimated accuracy of different machine learning algorithms effectively? In this post you will discover 8 techniques that you can use to compare machine learning algorithms in R. You can use these techniques to choose the most accurate model, and be able to comment on the statistical significance and the absolute […]

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Machine Learning Project Template in R

Applied machine learning is an empirical skill. You cannot get better at it by reading books and blog posts. You have to practice. In this post you will discover the simple 6-step machine learning project template that you can use to jump-start your project in R. Let’s get started. Practice Machine Learning With End-to-End Projects […]

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Getting Started with Microsoft SQL Server on Azure

by Joseph Rickert If you are an R user and work for an enterprise where Microsoft SQL server is important, it is extremely helpful to have easy access to SQL Server databases. Over the past year, we have run several posts on this topic including a comprehensive four part series from Microsoft's Gregory Vandenbrouck on using various flavors of SQL with Azure as a data source (Part1, Part2, Part3 and Part4) as well as several posts on using the advanced features of Microsoft R Server (formerly Revolution R Enterprise) with SQL Server 2016. (See for example this recent post Credit...

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Tutorial: Credit Card Fraud Detection with SQL Server 2016 R Services

If you have a database of credit-card transactions with a small percentage tagged as fraudulent, how can you create a process that automatically flags likely fraudulent transactions in the future? That's the premise behind the latest Data Science Deep Dive on MSDN. This tutorial provides a step by step to using the R language and the big-data statistical models of the RevoScaleR package of SQL Server 2016 R Services to build and use a predictive model to detect fraud. To follow along with the tutorial you'll need to install SQL Server 2016 and R Services on a database server, and...

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How To Load Your Machine Learning Data Into R

You need to be able to load data into R when working on a machine learning problem. In this short post, you will discover how you can load your data files into R and start your machine learning project. Let’s get started. Access To Your Data The most common way to work with data in […]

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