Data Mining

Just out: New Editions of Practical Time Series Forecasting (R and XLMiner)

I am glad to announce that the new editions of Practical Time Series Forecasting with R (Shmueli & Lichtendahl, Second Edition) and Practical Time Series Forecasting (Shmueli, Third Edition) are now available in print and ebook formats. The books are printed in the United States, Europe and India and are vailable globally. Kindle editions are also available worldwide.

3rd edition of "Data Mining for Business Analytics" now published

I'm glad to announce that the third edition of our textbook Data Mining for Business Analytics (with Peter Bruce and Nitin Patel) is now available! We added several cool and useful new topics: ensembles, uplift modeling, collaborative filtering, social network analysis, and text mining. The new edition also includes new examples and cases and XLMiner screenshots updated with the current software version.

Talk @ INFORMS: Trees for Detecting Simpson's Paradox in Big Data

Tomorrow at INFORMS's Data Mining Cluster @ 1:30pm, I'll be presenting my work (with Inbal Yahav) "The Forest or the Trees? Tackling Simpson’s Paradox with Classification and Regression Trees". I'll show the special use of the tree structure that we take advantage of in order to detect whether a dataset has Simpson's Paradox (reversal of a causal direction when disaggregating the data).

Tree based approach for addressing self-selection in Big Data: forthcoming in MIS Quarterly

My paper A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Big Data with Deepa Mani (Indian School of Business) and Inbal Yahav (Bar-Ilan University) is forthcoming in MIS Quarterly, in the special issue on Transformational Issues of Big Data and Analytics in Networked Business.


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