Titlebook: Soft Methods for Data Science; Maria Brigida Ferraro,Paolo Giordani,Olgierd Hryni Conference proceedings 2017 Springer International Publi

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Maximum Likelihood Under Incomplete Information: Toward a Comparison of Criteria,e or contain imprecise data, depending on the purpose, a major issue is to properly define the likelihood function to be maximized. This paper compares several proposals in terms of their intuitive appeal, showing their anomalous behavior on examples.

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The Use of Uncertainty to Choose Matching Variables in Statistical Matching,y based on a set of common variables shared by the available data sources. For matching purposes just a subset of all the common variables should be used, the so called matching variables. The paper presents a novel method for selecting the matching variables based on the analysis of the uncertainty

radiograph

2194-5357 gramming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science..978-3-319-42971-7978-3-319-42972-4Series ISSN 2194-5357 Series E-ISSN 2194-5365

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