book An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics) page full Books detail ●
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Title : book An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics) page full isbn : 1461471370
Book synopsis An Introduction to Statistical Learning This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.
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with Applications in R (Springer Texts in Statistics)
ggplot2: Elegant Graphics for Data Analysis (Use R!) Deep Learning (Adaptive Computation and Machine Learning Series) · Pattern Recognition and Machine Learning (Information Science and Statistics) · Hands-On Machine Learning with Scikit-Learn and TensorFlow · Python Machine Learning: Machine Learning and ...
approaches, tree-based methods, support vector machines, and clustering. ... Pattern Recognition and Machine Learning (Information Science and Statistics).
Try one of the apps below to open or edit this item. pdf-1424\theory-of-multivariate-statistics-springer-texts-in-statistics-by-martin-bilodeau-david-brenner.pdf.
approaches, tree-based methods, support vector machines, and clustering. Related. The Elements of Statistical Learning: Data Mining, Inference, and Prediction ...
