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Open AccessJournal ArticleDOI

Building Predictive Models in R Using the caret Package

Max Kuhn
- 10 Nov 2008 - 
- Vol. 28, Iss: 5, pp 1-26
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TLDR
The caret package, short for classification and regression training, contains numerous tools for developing predictive models using the rich set of models available in R to simplify model training and tuning across a wide variety of modeling techniques.
Abstract
The caret package, short for classification and regression training, contains numerous tools for developing predictive models using the rich set of models available in R. The package focuses on simplifying model training and tuning across a wide variety of modeling techniques. It also includes methods for pre-processing training data, calculating variable importance, and model visualizations. An example from computational chemistry is used to illustrate the functionality on a real data set and to benchmark the benefits of parallel processing with several types of models.

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Citations
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Journal ArticleDOI

Leaf to canopy upscaling approach affects the estimation of canopy traits

TL;DR: In remote sensing applications, leaf traits are often upscaled to canopy level using sunlit leaf samples collected from the upper canopy as mentioned in this paper, where the implicit assumption is that the top of canopy foliage m...
Journal ArticleDOI

Comparative analysis of rainfall prediction models using machine learning in islands with complex orography: Tenerife island

TL;DR: A comparative study between predictive monthly rainfall models for islands of complex orography using machine learning techniques shows that global predictors such as the North Atlantic Oscillation Index (NAO) have a very low influence, while the local Geopotential Height (GPH) predictor is relatively more important.
Journal ArticleDOI

Molecular diagnostics on the toxigenic potential of Fusarium spp. plant pathogens.

TL;DR: An efficient and rapid protocol for the detection of toxigenic Fusarium isolates producing three main types of Fus aquarium‐associated mycotoxins (fumonisins, trichothecenes and zearelanone) is proposed and tested.
Journal ArticleDOI

Germline cancer predisposition variants and pediatric glioma: a population-based study in California.

TL;DR: A considerable fraction of pediatric glioma patients, especially those of higher grade, harbor a putatively pathogenic variant in a cancer predisposition gene, and some of these variants may be clinically actionable or may warrant genetic counseling.
Journal ArticleDOI

Early Detection of Sage (Salvia officinalis L.) Responses to Ozone Using Reflectance Spectroscopy.

TL;DR: The capability of full-range (350–2500 nm) reflectance spectroscopy to characterize responses of asymptomatic sage leaves under an acute O3 exposure is demonstrated and O3-tolerance was confirmed by trends of vegetation indices and leaf traits derived from spectra, further highlighting the capability of reflectanceSpectra to early detect the responses of crops to O3.
References
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BookDOI

Modern Applied Statistics with S

TL;DR: A guide to using S environments to perform statistical analyses providing both an introduction to the use of S and a course in modern statistical methods.

Classification and Regression by randomForest

TL;DR: random forests are proposed, which add an additional layer of randomness to bagging and are robust against overfitting, and the randomForest package provides an R interface to the Fortran programs by Breiman and Cutler.

Modern Applied Statistics With S

TL;DR: The modern applied statistics with s is universally compatible with any devices to read, and is available in the digital library an online access to it is set as public so you can download it instantly.
Proceedings ArticleDOI

Validity of the single processor approach to achieving large scale computing capabilities

TL;DR: In this paper, the authors argue that the organization of a single computer has reached its limits and that truly significant advances can be made only by interconnection of a multiplicity of computers in such a manner as to permit cooperative solution.