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Home > Art, Film & Photography > Aprendizaje Automatico: Mineria de Datos, Demostracion Automatica de Teoremas, Aprendizaje Supervisado, Weka, Reglas de Asociacion
Aprendizaje Automatico: Mineria de Datos, Demostracion Automatica de Teoremas, Aprendizaje Supervisado, Weka, Reglas de Asociacion

Aprendizaje Automatico: Mineria de Datos, Demostracion Automatica de Teoremas, Aprendizaje Supervisado, Weka, Reglas de Asociacion


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About the Book

Fuente: Wikipedia. Paginas: 26. Capitulos: Mineria de datos, Demostracion automatica de teoremas, Aprendizaje supervisado, Weka, Reglas de asociacion, General Architecture for Text Engineering, Maquinas de vectores de soporte, Deep Blue, KNIME, Red neuronal de impulsos, Mineria de textos, KEEL, Analisis de afinidad, Aprendizaje no supervisado, Aprendizaje semisupervisado, Dimension VC, Maldicion de la dimension, Algoritmo de agrupamiento, RapidMiner, Mallet, Sobreajuste, Corpus linguistico, Matriz de confusion, Analisis de conceptos formales, Algoritmo apriori, Orange, Dendrograma, Demostracion interactiva de teoremas, PhoX, Espacio de versiones. Extracto: La mineria de datos (DM, Data Mining) consiste en la extraccion no trivial de informacion que reside de manera implicita en los datos. Dicha informacion era previamente desconocida y podra resultar util para algun proceso. En otras palabras, la mineria de datos prepara, sondea y explora los datos para sacar la informacion oculta en ellos. Bajo el nombre de mineria de datos se engloba todo un conjunto de tecnicas encaminadas a la extraccion de conocimiento procesable, implicito en las bases de datos. Esta fuertemente ligado con la supervision de procesos industriales ya que resulta muy util para aprovechar los datos almacenados en las bases de datos. Las bases de la mineria de datos se encuentran en la inteligencia artificial y en el analisis estadistico. Mediante los modelos extraidos utilizando tecnicas de mineria de datos se aborda la solucion a problemas de prediccion, clasificacion y segmentacion. Un proceso tipico de mineria de datos consta de los siguientes pasos generales: Si el modelo final no superara esta evaluacion el proceso se podria repetir desde el principio o, si el experto lo considera oportuno, a partir de cualquiera de los pasos anteriores. Esta retroalimentacion se podra repetir cuantas veces se considere necesario hasta obtener un modelo valido. Una vez validado el modelo, si resulta ser a...


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Product Details
  • ISBN-13: 9781232412076
  • Publisher: Books LLC
  • Publisher Imprint: Books LLC
  • Height: 246 mm
  • No of Pages: 28
  • Spine Width: 2 mm
  • Weight: 122 gr
  • ISBN-10: 1232412074
  • Publisher Date: 26 May 2011
  • Binding: Paperback
  • Language: Spanish
  • Returnable: N
  • Sub Title: Mineria de Datos, Demostracion Automatica de Teoremas, Aprendizaje Supervisado, Weka, Reglas de Asociacion
  • Width: 189 mm


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