## R.

Singular value decomposition (SVD) is explained using examples in R. SVD is a workhorse for techniques that decompose data, such as correspondence analysis.

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I show how to automatically fit the Support Vector Machine cost parameter by automating the manual search for the optimal cost.

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Although PLS and Johnson's Relative Weights are both techniques for dealing with correlations between predictors, they give fundamentally different results.

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Partial Least Squares in R is a great way to conduct relative importance analysis because it effectively compresses the data before regression.

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Partial Least Squares (PLS) is a popular method for relative importance analysis in fields where the data typically includes more predictors than observations. Relative importance analysis…

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This post describes the single biggest time saving technique that I know about for highlighting significant results on a table. That is just one table that show...

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Gradient boosting is attracting attention for its prediction speed & accuracy, especially with large & complex data. Here I show what it is and how to

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This post discusses a number of options that are available in R for analyzing data from MaxDiff experiments, using the package flipMaxDiff. For a more detailed…

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This post shows how to use correspondence analysis to compare sub-groups. It focuses on one of the most interesting types of sub-groups: data at different points…

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Correspondence analysis is a popular data science technique. It takes a large table, and turns it into a seemingly easy-to-read visualization. Unfortunately, it is not quite…

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Creating the experimental design for a max-diff experiment is easy in R. This post describes how to create and check a max-diff experimental design. If you are not sure what this is, it would be best to read A beginner’s guide to max-diff first.

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You can take your correspondence analysis plots to the next level by including images. This post describes how to create this plot using R.

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Labeled scatter plots and bubble charts can be easily formatted using the rhtmlLabeledScatter R package.

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Shapley regression has been gaining popularity in recent years and has been (re-)invented multiple times. However, relative weights, should be used instead.

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This posts describes how to create custom Sankey diagrams in R. It explains the basics of Sankey diagrams and provides examples of different layouts.

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To feed information about text into a statistical algorithm, it must first be converted into a form amenable to doing calculations - a term document matrix.

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Here are the seven steps to add an interactive R visualization to your blog post in under 30 seconds.

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