about
Data-derived modeling characterizes plasticity of MAPK signaling in melanomaIntegrated Modeling of Gene Regulatory and Metabolic Networks in Mycobacterium tuberculosisRandom Forests Are Able to Identify Differences in Clotting Dynamics from Kinetic Models of Thrombin GenerationIndividual differences in selective attention predict speech identification at a cocktail partyPatterns of crop cover under future climates.Towards Quantitative Spatial Models of Seabed Sediment Composition.Analyzing animal behavior via classifying each video frame using convolutional neural networks.Classification of sodium MRI data of cartilage using machine learningSex dependent risk factors for mortality after myocardial infarction: individual patient data meta-analysisRealizing the potential of mobile mental health: new methods for new data in psychiatryUsing decision trees to understand structure in missing data.Methods for the integration of multi-omics data: mathematical aspectsDiscovering governing equations from data by sparse identification of nonlinear dynamical systems.Long-Term Recovery of Microbial Communities in the Boreal Bryosphere Following Fire Disturbance.Using clinical data to predict high-cost performance coding issues associated with pressure ulcers: a multilevel cohort model.Promises, Pitfalls, and Basic Guidelines for Applying Machine Learning Classifiers to Psychiatric Imaging Data, with Autism as an Example.The Gulf of Aden Intermediate Water Intrusion Regulates the Southern Red Sea Summer Phytoplankton Blooms.The clinical status and economic savings associated with remission among patients with rheumatoid arthritis: leveraging linked registry and claims data for synergistic insights.Using data mining to predict success in a weight loss trial.Reshaping the epigenetic landscape during early flower development: induction of attractor transitions by relative differences in gene decay rates.The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients.Support Vector Machine Analysis of Functional Magnetic Resonance Imaging of Interoception Does Not Reliably Predict Individual Outcomes of Cognitive Behavioral Therapy in Panic Disorder with Agoraphobia.Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research.Predicting the outcomes of organic reactions via machine learning: are current descriptors sufficient?Batch effect confounding leads to strong bias in performance estimates obtained by cross-validation.The effect of mislabeled phenotypic status on the identification of mutation-carriers from SNP genotypes in dairy cattle.Physicians' perceived barriers to management of sexually transmitted infections in VietnamPredicting haplotype carriers from SNP genotypes in Bos taurus through linear discriminant analysisA systematic evaluation of high-dimensional, ensemble-based regression for exploring large model spaces in microbiome analyses.Physical function and quality of well-being in fibromyalgia: the applicability of the goodness-of-fit hypothesisAnalysis of environmental stress factors using an artificial growth system and plant fitness optimization.Assessing models for genetic prediction of complex traits: a comparison of visualization and quantitative methodsHigh-Frequency Heart Rate Variability Linked to Affiliation with a New Group.Inference of transcriptional regulation in cancers.Modelling aboveground forest biomass using airborne laser scanner data in the miombo woodlands of Tanzania.Predicting Human Cooperation.Sex Differences in Serum Markers of Major Depressive Disorder in the Netherlands Study of Depression and Anxiety (NESDA).Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging DataAdjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research.Predicting Subnational Ebola Virus Disease Epidemic Dynamics from Sociodemographic Indicators
P2860
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P2860
description
ouvrage
@fr
textbook
@en
uitgave van Trevor Hastie
@nl
name
An Introduction to Statistical Learning
@en
An Introduction to Statistical Learning
@fr
type
label
An Introduction to Statistical Learning
@en
An Introduction to Statistical Learning
@fr
altLabel
ISLR
@fr
prefLabel
An Introduction to Statistical Learning
@en
An Introduction to Statistical Learning
@fr
P50
P3181
P648
P136
P1476
An Introduction to Statistical Learning
@en
P1680
with Applications in R
@en
P212
978-1-4614-7137-0
978-1-4614-7138-7
P3181
P356
10.1007/978-1-4614-7138-7
P407
P577
2013-01-01T00:00:00Z
P648
OL26184759M