185 search results for "iris"

Reinventing the wheel for ordination biplots with ggplot2

May 14, 2015
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Reinventing the wheel for ordination biplots with ggplot2

I’ll be the first to admit that the topic of plotting ordination results using ggplot2 has been visited many times over. As is my typical fashion, I started creating a package for this purpose without completely searching for existing solutions. Specifically, the ggbiplot and factoextra packages already provide almost complete coverage of plotting results from

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Get data out of excel and into R with readxl

April 15, 2015
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excel_to_R

I’m pleased to announced that the first version of readxl is now available on CRAN. Readxl makes it easy to get tabular data out of excel. It: Supports both the legacy .xls format and the modern xml-based .xlsx format. .xls support is made possible the with libxls C library, which abstracts away many of the

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R User Group Recap: Heatmaps and Using the caret Package

April 10, 2015
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R User Group Recap: Heatmaps and Using the caret Package

At our most recent R user group meeting we were delighted to have presentations from Mark Lawson and Steve Hoang, both bioinformaticians at Hemoshear. All of the code used in both demos is in our Meetup’s GitHub repo.Making heatmaps in RSteve started with an overview of making heatmaps in R. Using the iris dataset, Steve demonstrated...

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readr 0.1.0

April 9, 2015
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readr 0.1.0

I’m pleased to announced that readr is now available on CRAN. Readr makes it easy to read many types of tabular data: Delimited files withread_delim(), read_csv(), read_tsv(), and read_csv2(). Fixed width files with read_fwf(), and read_table(). Web log files with read_log(). You can install it by running: install.packages("readr") Compared to the equivalent base functions, readr

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R Tutorial on Reading and Importing Excel Files into R

April 2, 2015
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R Tutorial on Reading and Importing Excel Files into R

Why an R Tutorial on Reading and Importing Excel Files into R is necessary As most of you know, Excel is a spreadsheet application developed by Microsoft. It is an easy accessible tool for organizing, analyzing and storing data in tables and has a widespread use in many different application fields all over the world. The post

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Seeing the Forest and the Trees – a parallel machine learning example

April 1, 2015
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Seeing the Forest and the Trees – a parallel machine learning example

Parallelizing Random Forests in R with BatchJobs and OpenLava By: Gord Sissons and Feng Li In his series of blogs about machine learning, Trevor Stephens focuses on a survival model from the Titanic disaster and provides a tutorial explaining how decision trees tend to over-fit models yielding anomalous predictions. How do we build a better

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Machine Learning in R for beginners

March 25, 2015
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Machine Learning in R for beginners

Introducing: Machine Learning in R Machine learning is a branch in computer science that studies the design of algorithms that can learn. Typical machine learning tasks are concept learning, function learning or “predictive modeling”, clustering and finding predictive patterns. These tasks are learned through available data that were observed through experiences or instructions, for example. The post

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“What You’re Doing Is Rather Desperate”

March 22, 2015
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“What You’re Doing Is Rather Desperate”

Self-protrait by Gustave Courbet.Source: WikiMedia Commons.One blog that I have been (occasionally but repeatedly) reading for a long time is the What You're Doing Is Rather Desperate blog by Neil Saunders. HT to WoW!ter for po...

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Aggregation

February 26, 2015
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Aggregation splits data into subsets, computes summary statistics on each subset, and reports the results in a conveniently summarized form. The aggregate function is one of the most capable functions in the scidb package. The package overloads R’s standard aggregate function for SciDB arrays, using reasonably standard R syntax to cover most SciDB aggregation operators The post

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More on Quadratic Progarmming in R

February 10, 2015
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More on Quadratic Progarmming in R

This post is another tour of quadratic programming algorithms and applications in R. First, we look at the quadratic program that lies at the heart of support vector machine (SVM) classification. Then we'll look at a very different quadratic programming demo problem that models the energy of a circus tent. The key...

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