Dataset Shift in Machine Learning pdf epub mobi txt 電子書 下載 2024


Dataset Shift in Machine Learning

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Quinonero-candela, Joaquin (EDT)/ Sugiyama, Masashi (EDT)/ Schwaighofer, Anton (EDT)/ Lawrence, Neil
The MIT Press
2008-12-12
248
USD 40.00
Hardcover
9780262170055

圖書標籤: 機器學習  learning  data  Dataset  shift  machine  in  ebook   


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发表于2024-12-23

Dataset Shift in Machine Learning epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

Dataset Shift in Machine Learning epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

Dataset Shift in Machine Learning pdf epub mobi txt 電子書 下載 2024



圖書描述

Dataset shift is a common problem in predictive modeling that occurs when the joint distribution of inputs and outputs differs between training and test stages. Covariate shift, a particular case of dataset shift, occurs when only the input distribution changes. Dataset shift is present in most practical applications, for reasons ranging from the bias introduced by experimental design to the irreproducibility of the testing conditions at training time. (An example is -email spam filtering, which may fail to recognize spam that differs in form from the spam the automatic filter has been built on.) Despite this, and despite the attention given to the apparently similar problems of semi-supervised learning and active learning, dataset shift has received relatively little attention in the machine learning community until recently. This volume offers an overview of current efforts to deal with dataset and covariate shift. The chapters offer a mathematical and philosophical introduction to the problem, place dataset shift in relationship to transfer learning, transduction, local learning, active learning, and semi-supervised learning, provide theoretical views of dataset and covariate shift (including decision theoretic and Bayesian perspectives), and present algorithms for covariate shift. Contributors [cut for catalog if necessary]Shai Ben-David, Steffen Bickel, Karsten Borgwardt, Michael Bruckner, David Corfield, Amir Globerson, Arthur Gretton, Lars Kai Hansen, Matthias Hein, Jiayuan Huang, Choon Hui Teo, Takafumi Kanamori, Klaus-Robert Muller, Sam Roweis, Neil Rubens, Tobias Scheffer, Marcel Schmittfull, Bernhard Scholkopf Hidetoshi Shimodaira, Alex Smola, Amos Storkey, Masashi Sugiyama

Dataset Shift in Machine Learning 下載 mobi epub pdf txt 電子書

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Dataset Shift in Machine Learning pdf epub mobi txt 電子書 下載
想要找書就要到 小哈圖書下載中心
立刻按 ctrl+D收藏本頁
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用戶評價

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可以說是關於covariate shift的論文集,未來隨著算法研究越來越深,這部分的影響應該會越來越大

評分

不錯的論文集,但內容概念有點過時。

評分

快快的瀏覽瞭一下,對於論文集形式的書來說不錯瞭,入門讀物,KMM及之後部分感覺寫的相對好

評分

可以說是關於covariate shift的論文集,未來隨著算法研究越來越深,這部分的影響應該會越來越大

評分

可以說是關於covariate shift的論文集,未來隨著算法研究越來越深,這部分的影響應該會越來越大

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Dataset Shift in Machine Learning pdf epub mobi txt 電子書 下載 2024


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