text mining predictive methods von weiss sholom (11 Ergebnisse)

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Zustand: Bueno. : Este libro explora el campo del 'Text Mining', centrándose en métodos predictivos para analizar información no estructurada. Aborda cómo transformar texto y documentos en valores medibles, aplicando técnicas de minería de datos predictiva. Se discuten las adaptaciones necesarias en las técnicas de evaluación, considerando el orden cronológico de publicación y medidas de error alternativas, así como la modificación de métodos para manejar grandes volúmenes de datos. EAN: 9780387954332 Tipo: Libros Categoría: Tecnología|Ciencias Título: Text Mining: Predictive Methods for Analyzing Unstructured Information Autor: Sholom M. Weiss| Nitin Indurkhya| Tong Zhang| Fred Damerau Editorial: Springer Idioma: en Páginas: 249 Formato: tapa dura.

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Taschenbuch. Zustand: Neu. Text Mining | Predictive Methods for Analyzing Unstructured Information | Sholom M. Weiss (u. a.) | Taschenbuch | xii | Englisch | 2010 | Springer US | EAN 9781441929969 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Data mining is a mature technology. The prediction problem, looking for predictive patterns in data, has been widely studied. Strong me- ods are available to the practitioner. These methods process structured numerical information, where uniform measurements are taken over a sample of data. Text is often described as unstructured information. So, it would seem, text and numerical data are different, requiring different methods. Or are they In our view, a prediction problem can be solved by the same methods, whether the data are structured - merical measurements or unstructured text. Text and documents can be transformed into measured values, such as the presence or absence of words, and the same methods that have proven successful for pred- tive data mining can be applied to text. Yet, there are key differences. Evaluation techniques must be adapted to the chronological order of publication and to alternative measures of error. Because the data are documents, more specialized analytical methods may be preferred for text. Moreover, the methods must be modi ed to accommodate very high dimensions: tens of thousands of words and documents. Still, the central themes are similar.

Buch. Zustand: Neu. Neuware - Data mining is a mature technology. The prediction problem, looking for predictive patterns in data, has been widely studied. Strong me- ods are available to the practitioner. These methods process structured numerical information, where uniform measurements are taken over a sample of data. Text is often described as unstructured information. So, it would seem, text and numerical data are different, requiring different methods. Or are they In our view, a prediction problem can be solved by the same methods, whether the data are structured - merical measurements or unstructured text. Text and documents can be transformed into measured values, such as the presence or absence of words, and the same methods that have proven successful for pred- tive data mining can be applied to text. Yet, there are key differences. Evaluation techniques must be adapted to the chronological order of publication and to alternative measures of error. Because the data are documents, more specialized analytical methods may be preferred for text. Moreover, the methods must be modi ed to accommodate very high dimensions: tens of thousands of words and documents. Still, the central themes are similar.