223 search results for "iris"

Using PostgreSQL in R: A quick how-to

February 1, 2016
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Using PostgreSQL in R: A quick how-to

The combination of R plus SQL offers an attractive way to work with what we call medium-scale data: data that’s perhaps too large to gracefully work with in its entirety within your favorite desktop analysis tool (whether that be R or Excel), but too small to justify the overhead of big data infrastructure. In some … Continue reading...

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Hierarchical Clustering in R

January 22, 2016
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Hierarchical Clustering in R

Hello everyone! In this post, I will show you how to do hierarchical clustering in R. We will use the iris dataset again, like we did for K means clustering. What is hierarchical clustering? If you recall from the post about k means clustering, it requires us to specify the number of clusters, and finding

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Fun Data for teaching R

January 21, 2016
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Fun Data for teaching R

I’ll be running an R course soon and I am looking for fun (public) datasets to use in data manipulation and visualization. I would like to use a single dataset that has some easy variables for the first days, but … Continue reading →

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A gentle introduction to parallel computing in R

January 18, 2016
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A gentle introduction to parallel computing in R

Let’s talk about the use and benefits of parallel computation in R. IBM’s Blue Gene/P massively parallel supercomputer (Wikipedia). Parallel computing is a type of computation in which many calculations are carried out simultaneously.” Wikipedia quoting: Gottlieb, Allan; Almasi, George S. (1989). Highly parallel computing The reason we care is: by making the computer work … Continue reading...

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Presenting Highcharter

January 13, 2016
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Presenting Highcharter

After a lot of documentation, a lot of R CMD checks and a lot of patience from CRAN people I'm happy to anonounce highcharter v0.1.0: A(nother) wrapper for Highcharts charting library. Now it's easy make a chart like this. Do you want to know how? I like Highcharts. It was the first charting javascript library what I used...

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R Users Will Now Inevitably Become Bayesians

January 12, 2016
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R Users Will Now Inevitably Become Bayesians

There are several reasons why everyone isn’t using Bayesian methods for regression modeling. One reason is that Bayesian modeling requires more thought: you need pesky things like priors, and you can’t assume that if a procedure runs without throwing an … Continue reading →

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Sampling Arbitrary data

January 3, 2016
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Sampling Arbitrary data

Introduction:Generating data usually requires a variance - covariance matrix and is therefore restricted by using a linear assumption between the variables. However, using a linear assumption between data can miss important non - linear relationships. ...

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Factor exercises

December 28, 2015
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In the exercises below we cover the basics of factors. Before proceeding, first read chapter 4 of An Introduction to R, and the help pages for the cut, and table functions. Answers to the exercises are available here. Exercise 1 If x = c(1, 2, 3, 3, 5, 3, 2, 4, NA), what are the

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K Means Clustering in R

December 28, 2015
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K Means Clustering in R

Hello everyone, hope you had a wonderful Christmas! In this post I will show you how to do k means clustering in R. We will use the iris dataset from the datasets library. What is K Means Clustering? K Means Clustering is an unsupervised learning algorithm that tries to cluster data based on their similarity.

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ggplot 2.0.0

December 22, 2015
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I’m very pleased to announce the release of ggplot2 2.0.0. I know I promised that there wouldn’t be any more updates, but while working on the 2nd edition of the ggplot2 book, I just couldn’t stop myself from fixing some long standing problems. On the scale of ggplot2 releases, this one is huge with over

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