9781441929969 - text mining: predictive methods for analyzing unstructured information di weiss, sholom m. m.; indurkhya, nitin; zhang, tong; damerau, fred (11 risultati)
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Text Mining: Predictive Methods for Analyzing Unstructured Information
Weiss, Sholom M. M.; Indurkhya, Nitin; Zhang, Tong; Damerau, Fred
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Taschenbuch. Condizione: Neu. Text Mining | Predictive Methods for Analyzing Unstructured Information | Sholom M. Weiss (u. a.) | Taschenbuch | xii | Englisch | 2010 | Springer | EAN 9781441929969 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]…com | Anbieter: preigu.
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Condizione: New. pp. 252.
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Taschenbuch. Condizione: 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 m…easurements 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.
Text Mining: Predictive Methods for Analyzing Unstructured Information
Weiss, Sholom M., Indurkhya, Nitin, Zhang, Tong, Damerau, Fr
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 252 pp. Englisch.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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, whe…re 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 252 pp. Englisch.
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Condizione: New. Print on Demand pp. 252 79 Illus.
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 252.
