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Cargando... Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discoverypor Graham Williams
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Inscríbete en LibraryThing para averiguar si este libro te gustará. Actualmente no hay Conversaciones sobre este libro. There are a few, or maybe several, GUIs for R - R commander, an R Excel plug-in, etc. Rattle is an interface for doing data mining. The book explains things in a straight-forward and practical way, and the interface is pretty cool. My favorite thing is the log which shows you all of the R-code, so you can see which library and functions are used to generate your results. ( ) sin reseñas | añadir una reseña
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Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of data, the choice of tools, and the choice of algorithms. Throughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built on the sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment. The reader will learn to rapidly deliver a data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data mining environment with all the power, and more, of the many commercial offerings. No se han encontrado descripciones de biblioteca. |
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Google Books — Cargando... GénerosSistema Decimal Melvil (DDC)006.312Information Computer Science; Knowledge and Systems Special Topics Artificial Intelligence Machine LearningClasificación de la Biblioteca del CongresoValoraciónPromedio:
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