Download Discovering Knowledge in Data: An Introduction to Data by Daniel T. Larose, Chantel D. Larose PDF

By Daniel T. Larose, Chantel D. Larose

ISBN-10: 1118873580

ISBN-13: 9781118873588

The second one variation of a hugely praised, winning reference on information mining, with thorough insurance of huge information purposes, predictive analytics, and statistical analysis.

Includes new chapters on:
• Multivariate Statistics
• getting ready to version the information, and
• Imputation of lacking facts, and
• an Appendix on facts Summarization and Visualization

• bargains broad assurance of the R statistical programming language
• comprises 280 end-of-chapter exercises
• contains a spouse site with additional assets for all readers, and
• Powerpoint slides, a suggestions guide, and recommended initiatives for teachers who undertake the publication

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Extra resources for Discovering Knowledge in Data: An Introduction to Data Mining (2nd Edition)

Example text

Finally, the internal heterogeneity of VGI data sets that are assembled through the collaborative efforts of many volunteers complicates value assessments. In particular, the standard approaches for evaluating data accuracy and completeness 2 Understanding the Value of VGI 23 referred to earlier were designed to apply to GI that was produced entirely by a single author or entity. Notwithstanding the self-policing nature of communities engaged in user-generated content, data quality can vary substantially between contributors to a given data set.

1999). The cathedral and the bazaar: Musings on Linux and open source by an accidental revolutionary. Cambridge, MA: O’Reilly. , & Loomis, J. (2009). The total economic value of threatened, endangered and rare species: An updated meta-analysis. Ecological Economics, 68, 1535–1548. Roche, S. (2011). De la cartographie participative aux WikiSIG. In O. Walser, L. Thévoz, F. Joerin, M. Schuler, S. Joost, B. Debarbieux, & H. ), Les SIG au service du développement territorial (pp. 117–129). Lausanne: Presses polytechniques et universitaires romandes.

This improvement is another characteristic of the social value of VGI. Improving spatial enablement, for a group of people, or even an organization or the society itself, is part of geosocial added value. The high profile examples mentioned above illustrate that it is possible to at least approximate the relative value of certain types of VGI. g. privacy encroachments) of VGI accrue is more problematic. This is due in part to the fact that, more than its authoritative counterparts, VGI’s value is a function of both the intrinsic characteristics of the data that citizen volunteers create and the socio-technological processes through which these data are produced and used.

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Discovering Knowledge in Data: An Introduction to Data Mining (2nd Edition) by Daniel T. Larose, Chantel D. Larose

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