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  2. Gareth M. James - Wikipedia

    en.wikipedia.org/wiki/Gareth_M._James

    James is a noted scholar and researcher. His extensive published works include numerous articles, conference proceedings, and book chapters focused on statistical and machine learning methodologies. His work has been cited more than 20,000 times. James is also co-author of the extremely successful textbook, An Introduction to Statistical Learning.

  3. Trevor Hastie - Wikipedia

    en.wikipedia.org/wiki/Trevor_Hastie

    G. James, D. Witten, T. Hastie, R. Tibshirani, An Introduction to Statistical Learning with Applications in R, Springer Verlag, 2013 [10] (available for free from the co-author's website). T. Hastie, R. Tibshirani, M. Wainwright, Statistical Learning with Sparsity: the Lasso and Generalizations , CRC Press, 2015 [ 11 ] (available for free from ...

  4. Daniela Witten - Wikipedia

    en.wikipedia.org/wiki/Daniela_Witten

    She was awarded the American Statistical Association David P. Byar Young Investigator Award for her work Penalized Classification Using Fisher’s Linear Discriminant in 2011. [22] Her book An Introduction to Statistical Learning won a Technometrics Ziegel Award in 2014. [23] She won an Elle magazine Genius Award in 2012. [24]

  5. Robert Tibshirani - Wikipedia

    en.wikipedia.org/wiki/Robert_Tibshirani

    G. James, D. Witten, T. Hastie, R. Tibshirani, An Introduction to Statistical Learning with Applications in R, Springer Verlag, 2013 [8] (available for free from the co-author's website). T. Hastie, R. Tibshirani, M. Wainwright, Statistical Learning with Sparsity: the Lasso and Generalizations , CRC Press, 2015 [ 9 ] (available for free from ...

  6. Statistical learning theory - Wikipedia

    en.wikipedia.org/wiki/Statistical_learning_theory

    Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [ 1 ] [ 2 ] [ 3 ] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data.

  7. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  8. Dad shares bittersweet video of when his 13-year-old ...

    www.aol.com/dad-shares-bittersweet-video-13...

    Donovan McDaniel's son Maverick uncovered the truth about Santa and confronted his dad in a viral video.

  9. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data analysis focuses on extracting insights and drawing conclusions from structured data, while data science involves a more comprehensive approach that combines statistical analysis, computational methods, and machine learning to extract insights, build predictive models, and drive data-driven decision-making. Both fields use data to ...

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