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This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and …
Knowledge to be mined (or: Data mining functions) • Characterization, discrimination, association, classification, clustering, trend/deviation, outlier analysis, etc. • Descriptive …
The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data …
Machine learning and data mining techniques have countless applications, including data science applications, and this reference is essential for anyone seeking quick access to …
The book presents a coherent and unified repository of data science and machine learning major concepts, theories, methods, trends and challenges.
See more on infolab.stanford.edu
WEBData Mining and Machine Learning: Fundamental Concepts and Algorithms. Second Edition Mohammed J. Zaki and Wagner Meira, Jr Cambridge University Press, March …
Machine learning provides a wide selection of options by which to answer these questions, along with the vast experience of the community as to which methods tend to be …
We will use this notation for our data matrix and the rows of X will correspond to N observations and the M columns of X will correspond to M attributes. Often each of the …
Zaki & Meira Jr. (RPI and UFMG) Data Mining and Machine Learning Chapter 1: Data Mining and Analysis 1/24 Data Matrix Data can often be represented or abstracted as an …
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