Statistical Methods for Imbalanced Data in Ecological and Biological Studies. 1st ed. 2019

種類:

電子ブック

責任表示:

by Osamu Komori, Shinto Eguchi

出版情報:

Tokyo : Springer Japan : Imprint: Springer, 2019

著者名:

• Komori, Osamu.
• Eguchi, Shinto.
• SpringerLink (Online service)

シリーズ名:

JSS Research Series in Statistics ;

ISBN:

9784431555704 [4431555706]    

注記:

1. Imbalance Data -- 2. Weighted Logistic Regression -- 3. Beta-Maxent -- 4. Generalized-t Statistic -- 5. Machine Learning Methods for Imbalance Data.
This book presents a fresh, new approach in that it provides a comprehensive recent review of challenging problems caused by imbalanced data in prediction and classification, and also in that it introduces several of the latest statistical methods of dealing with these problems. The book discusses the property of the imbalance of data from two points of view. The first is quantitative imbalance, meaning that the sample size in one population highly outnumbers that in another population. It includes presence-only data as an extreme case, where the presence of a species is confirmed, whereas the information on its absence is uncertain, which is especially common in ecology in predicting habitat distribution. The second is qualitative imbalance, meaning that the data distribution of one population can be well specified whereas that of the other one shows a highly heterogeneous property. A typical case is the existence of outliers commonly observed in gene expression data, and another is heterogeneous characteris

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