New PDF release: Statistical Learning and Data Science (Computer Science &

By Fionn Murtagh, Mireille Gettler Summa, Leon Bottou, Bernard Goldfarb, Catherine Pardoux, Myriam Touati

ISBN-10: 1439867631

ISBN-13: 9781439867631

Data research is altering speedy. pushed via an unlimited diversity of program domain names and reasonable instruments, laptop studying has develop into mainstream. Unsupervised facts research, together with cluster research, issue research, and occasional dimensionality mapping tools regularly being up-to-date, have reached new heights of accomplishment within the particularly wealthy info international that we inhabit.

Statistical studying and information Science is a piece of reference within the quickly evolving context of converging methodologies. It gathers contributions from many of the foundational thinkers within the varied fields of knowledge research to the key theoretical ends up in the area. at the methodological entrance, the quantity comprises conformal prediction and frameworks for assessing self assurance in outputs, including attendant danger. It illustrates a variety of purposes, together with semantics, credits chance, strength construction, genomics, and ecology. The publication additionally addresses problems with starting place and evolutions within the unsupervised info research enviornment, and offers a few methods for time sequence, symbolic information, and useful data.

Over the heritage of multidimensional facts research, progressively more advanced information became on hand for processing. Supervised computer studying, semi-supervised research methods, and unsupervised info research, supply nice potential for addressing the electronic info deluge. Exploring the principles and up to date breakthroughs within the box, Statistical studying and information Science demonstrates how info research can increase own and collective health and wellbeing and the health and wellbeing of our social, company, and actual environments.

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Additional resources for Statistical Learning and Data Science (Computer Science & Data Analysis Series)

Sample text

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 30 31 32 34 34 36 38 38 39 39 41 41 42 In the Learning Using Privileged Information (LUPI) model, along with standard training data in the primary space, a teacher supplies a student with additional (privileged) information in the secondary space. The goal of the learner is to find a classifier with a low generalization error in the primary space.

Learning with Large Training Sets . . . . . . . . . . . . . . . . . . . . . . . 1 The Tradeoffs of Large-Scale Learning . . . . . . . . . . . . . . . . 2 Asymptotic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . Efficient Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Experiments . . . . . . . . . . .

6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 30 31 32 34 34 36 38 38 39 39 41 41 42 In the Learning Using Privileged Information (LUPI) model, along with standard training data in the primary space, a teacher supplies a student with additional (privileged) information in the secondary space.

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Statistical Learning and Data Science (Computer Science & Data Analysis Series) by Fionn Murtagh, Mireille Gettler Summa, Leon Bottou, Bernard Goldfarb, Catherine Pardoux, Myriam Touati


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