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CS 412: Introduction to Data Mining Course Syllabus Course Description This course is an introductory course on data mining. It introduces the basic concepts, principles, methods, implementation techniques, and applications of data mining, with a focus on two major data mining functions: (1) pattern discovery and (2) cluster analysis.

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Data Mining Sanjay Ranka Spring 2011 Data Mining Tasks • Prediction methods – Use some variables to predict unknown or future values of the same or other variables • Description methods – Find human interpretable patterns that describe data From Fayyad, et al., Advances in Knowledge Discovery and Data Mining, 1996

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also introduced a large-scale data-mining project course, CS341. The book now contains material taught in all three courses. What the Book Is About At the highest level of description, this book is about data mining. However, it focuses on data mining of very large amounts of data, that is, data so large it does not fit in main memory.

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The data has been randomly partitioned into 3 parts- Training Data (1800 customers): initial data to be used to fit response models, Validation Data (1400 customers): hold-out data used to compare the performance of different response models, and Test Data (800 Customers): data only to be used after a final model has been selected to estimate ...

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This book presents fundamental concepts and algorithms for those learning data mining for the first time. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms. - free book at FreeComputerBooks.com - download here

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each outcome from the data, then this is more like the problems considered by data mining. However, in this specific case, solu-tions to this problem were developed by mathematicians a long time ago, and thus, we wouldn't consider it to be data mining. (f) Predicting the future stock price of a company using historical records. Yes.

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data mining should have been called "knowledge mining" instead. Nevertheless, data mining became the accepted customary term, and very rapidly a trend that even overshadowed more general terms such as knowledge discovery in databases (KDD) that describe a more complete process. Other similar terms referring to data mining are: data

Statistical Aspects of Data Mining (Stats 202) Day 1 - YouTube

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Data Mining Techniques 3 Fig. 1. The data mining process. In fact, the goals of data mining are often that of achieving reliable prediction and/or that of achieving understandable description. The former answers the question what", while the latter the question why". With respect to the goal of reliable prediction, the key criteria is that of ...

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XLMiner is a comprehensive data mining add-in for Excel, which is easy to learn for users of Excel. It is a tool to help you get quickly started on data mining, ofiering a variety of methods to analyze data. It has extensive coverage of statistical and data mining techniques for classiflcation, prediction, a–nity analysis, and data ...

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