Building Predictive Models in R Using the caret Package
Reads0
Chats0
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.read more
Citations
More filters
Proceedings ArticleDOI
Lightweight, Early Identification of At-Risk CS1 Students
TL;DR: A methodology for creating models, based on in-class clicker questions, to predict cross-term student performance and is capable of correctly predicting students as being in danger of failing, or not, for 70% of the students.
Journal ArticleDOI
Childhood vaccines and antibiotic use in low- and middle-income countries.
Joseph A Lewnard,Nathan Lo,Nimalan Arinaminpathy,Isabel Frost,Isabel Frost,Ramanan Laxminarayan,Ramanan Laxminarayan +6 more
TL;DR: Pneumococcal and rotavirus vaccines have reduced antibiotic consumption substantially among children under five years old in low- and middle-income countries; however, this effect could be doubled if all countries were to implement vaccination programmes and meet universal vaccine coverage targets.
Journal ArticleDOI
A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States
Kristin B. Byrd,L. Ballanti,Nathan Thomas,Dung Nguyen,James R. Holmquist,Marc Simard,Lisamarie Windham-Myers +6 more
TL;DR: In this paper, the authors developed the first calibration-grade, national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content in the conterminous United States (CONUS).
Journal ArticleDOI
Assessing soil organic carbon stocks under current and potential forest cover using digital soil mapping and spatial generalisation
TL;DR: In this paper, the authors used boosted regression trees (BRT), artificial neural networks (ANN) and least-squares support vector machines (LS-SVM) to estimate the organic carbon stock in the upper meter of forest in the region of Flanders (N. Belgium).
Journal ArticleDOI
Comparison between random forest and gradient boosting machine methods for predicting Listeria spp. prevalence in the environment of pastured poultry farms.
TL;DR: The developed models can be used to predict the prevalence of Listeria spp.
References
More filters
BookDOI
Modern Applied Statistics with S
W. N. Venables,Brian D. Ripley +1 more
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
Andy Liaw,Matthew C. Wiener +1 more
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.