# Posts Tagged ‘ r-project ’

## Compare performance of machine learning classifiers in R

December 23, 2009
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This tutorial demonstrates to the R novice how to create five machine learning models for classification and compare the performance graphically with ROC curves in one chart. For a simpler introduction, start with Plot ROC curve and lift chart in R. # ...

## Plot ROC curve and lift chart in R

December 18, 2009
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This tutorial with real R code demonstrates how to create a predictive model using cforest (Breiman’s random forests) from the package party, evaluate the predictive model on a separate set of data, and then plot the performance using ROC curves ...

## R Tutorial Series: Graphic Analysis of Regression Assumptions

December 15, 2009
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An important aspect of regression involves assessing the tenability of the assumptions upon which its analyses are based. This tutorial will explore how R can help one scrutinize the regression assumptions of a model via its residuals plot, normality h...

## R Tutorial Series: Multiple Linear Regression

December 8, 2009
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In R, multiple linear regression is only a small step away from simple linear regression. In fact, the same lm() function can be used for this technique, but with the addition of a one or more predictors. This tutorial will explore how R can be used to...

## R Tutorial Series: Simple Linear Regression

November 26, 2009
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Simple linear regression uses a solitary independent variable to predict the outcome of a dependent variable. By understanding this, the most basic form of regression, numerous complex modeling techniques can be learned. This tutorial will explore how ...

## R Tutorial Series: Scatterplots

November 12, 2009
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A scatterplot is a useful way to visualize the relationship between two variables. Similar to correlations, scatterplots are often used to make initial diagnoses before any statistical analyses are conducted. This tutorial will explore the ways in whic...

## R Tutorial Series: Zero-Order Correlations

November 6, 2009
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One of the most common and basic techniques for analyzing the relationships between variables is zero-order correlation. This tutorial will explore the ways in which R can be used to employ this method.Tutorial FilesBefore we start, you may want to dow...

## R has a JSON package

November 5, 2009
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Named rjson, appropriately. It’s quite basic just now, but contains methods for interconversion between R objects and JSON. Something like this: > library(rjson) > data <- list(a=1,b=2,c=3) > json <- toJSON(data) > json "{\"a\":1,\"b\":2,\"c\":3}" > cat(json, file="data.json") Use cases? I wonder if RApache could be used to build an API that serves R data in JSON format? Posted in

## R Tutorial Series: Summary and Descriptive Statistics

November 1, 2009
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Summary (or descriptive) statistics are the first figures used to represent nearly every dataset. They also form the foundation for much more complicated computations and analyses. Thus, in spite of being composed of simple methods, they are essential ...

## R Tutorial Series: Introduction to The R Project for Statistical Computing (Part 2)

October 15, 2009
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Welcome to part two of the Introduction to The R Project for Statistical Computing tutorial. If you missed part one, it can be found here. In this segment, we will explore the following topics.Importing DataVariablesWorkspace FilesConsole FilesFinding ...