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The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

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It is our great pleasure to welcome you to the 38th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems PODS 2019, held in Amsterdam, The Netherlands, on July 1- 3, 2019, in conjunction with the 2019 ACM SIGMOD International Conference on Management of Data. Since the first edition of the symposium in 1982, the PODS papers are distinguished by a rigorous approach to widely diverse problems in data management, often bringing to bear techniques from a variety of different areas, including computational logic, finite model theory, computational complexity, algorithm design and analysis, programming languages, and artificial intelligence. The PODS Symposia study data management challenges in a variety of application contexts, including more recently parallel computation, streaming and realtime data, and graph data processing algorithms. PODS has a tradition of being the premier international conference on the theoretical and foundational aspects of data management, and the interested reader is referred to the web page https://databasetheory.org/pods for information on the history of this conference series. This year's symposium continues this tradition and invited for submission papers providing original, substantial contributions in one or more of the following categories: a deep theoretical exploration of topical areas central to data management; b new formal frameworks that aim at providing a basis for deeper theoretical investigation of important emerging issues in data management; and c validation of theoretical approaches from the lens of practical applicability in data management. Papers in this track should provide an experimental evaluation that gives new insight in established theories. Besides, they should provide a clear message to the database theory community as to which aspects need further theoretical investigation, based on the experimental findings. As in previous years, PODS operated with two submission cycles. The first cycle allowed for the possibility for papers to be revised and resubmitted. For the first cycle, 36 papers were submitted, 4 of which were directly selected for inclusion in the proceedings, and 8 were invited for a resubmission after a revision. The quality of the revised papers increased substantially with respect to the first submission, and all of the revised papers were selected for the proceedings. For the second cycle, 51 papers were submitted, 17 of which were selected, resulting in 29 papers selected overall from a total number of 87 submissions. The program committee invited two tutorials, by Alan Fekete University of Sydney and by Suresh Venkatasubrahmanian University of Utah. In addition, it selected two "Gems of PODS" speakers, Christos Papadimitriou Columbia University and Leopoldo Bertossi Carleton University. "Gems of PODS" is an event, started in 2016, whose goal is to promote understanding of past seminal PODS results to the general audience. The Gems of PODS papers were selected by the Gems of PODS committee consisting of Mahmoud Abo Khamis, Christoph Koch chair, Pierre Senellart, and Yufei Tao. This volume contains the proceedings of PODS 2019, which include papers on the keynote addressed by Cynthia Dwork of Harvard University, the two invited tutorials, one of the two Gems talks, and 29 contributions that were selected by the Program Committee for presentation at the symposium.

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Database management.