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 characteristics often observed in a case group in case-control studies. The extension of the logistic regression model, maxent, and AdaBoost for imbalanced data is discussed, providing a new framework for improvement of prediction, classification, and performance of variable selection. Weights functions introduced in the methods play an important role in alleviating the imbalance of data. This book also furnishes a new perspective on these problem and shows some applications of the recently developed statistical methods to real data sets.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Osamu Komori, The Institute of Statistical Mathematics,
Shinto Eguchi, The Institute of Statistical Mathematics
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
Condizione: new. Questo è un articolo print on demand. Codice articolo f2243e7b0149f77c4b83a3d9d1be2941
Quantità: Più di 20 disponibili
Da: Chiron Media, Wallingford, Regno Unito
PF. Condizione: New. Codice articolo 6666-IUK-9784431555698
Quantità: 10 disponibili
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 characteristics often observed in a case group in case-control studies. The extension of the logistic regression model, maxent, and AdaBoost for imbalanced data is discussed, providing a new framework for improvement of prediction, classification, and performance of variable selection. Weights functions introduced in the methods play an important role in alleviating the imbalance of data. This book also furnishes a new perspective on these problem and shows some applications of the recently developed statistical methods to real data sets. 68 pp. Englisch. Codice articolo 9784431555698
Quantità: 2 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In English. Codice articolo ria9784431555698_new
Quantità: Più di 20 disponibili
Da: Books Puddle, Woodside, NY, U.S.A.
Condizione: New. pp. 100. Codice articolo 26372420635
Quantità: 4 disponibili
Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand pp. 100. Codice articolo 373624772
Quantità: 4 disponibili
Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. 1st edition. 59 pages. 9.25x6.25x0.50 inches. In Stock. Codice articolo x-4431555692
Quantità: 2 disponibili
Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND pp. 100. Codice articolo 18372420625
Quantità: 4 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 characteristics often observed in a case group in case-control studies. The extension of the logistic regression model, maxent, and AdaBoost for imbalanced data is discussed, providing a new framework for improvement of prediction, classification, and performance of variable selection. Weights functions introduced in the methods play an important role in alleviating the imbalance of data. This book also furnishes a new perspective on these problem and shows some applications of the recently developed statistical methods to real data sets. Codice articolo 9784431555698
Quantità: 1 disponibili
Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Osamu Komori, The Institute of Statistical Mathematics, Shinto Eguchi, The Institute of Statistical MathematicsThis book presents a fresh, new approach in that it provides a comprehensive recent review of challenging problems caused by imba. Codice articolo 38736129
Quantità: Più di 20 disponibili