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Titlebook: Discrimination and Privacy in the Information Society; Data Mining and Prof Bart Custers,Toon Calders,Tal Zarsky Book 2013 Springer-Verlag

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樓主: hector
41#
發(fā)表于 2025-3-28 14:40:41 | 只看該作者
https://doi.org/10.1007/978-94-007-7161-1mining emerged. In this chapter we position data mining with respect to other data analysis techniques and introduce the most important classes of techniques developed in the area: pattern mining, classification, and clustering and outlier detection. Also related, supporting techniques such as pre-processing and database coupling are discussed.
42#
發(fā)表于 2025-3-28 22:31:25 | 只看該作者
What Is Data Mining and How Does It Work?mining emerged. In this chapter we position data mining with respect to other data analysis techniques and introduce the most important classes of techniques developed in the area: pattern mining, classification, and clustering and outlier detection. Also related, supporting techniques such as pre-processing and database coupling are discussed.
43#
發(fā)表于 2025-3-28 22:58:06 | 只看該作者
Informal Housing and Marginal Settlementsrights, that is, embodying the logic of negative freedom..The final section will examine situations of overlap between the rights, building upon the Huber and Test-Achats cases. This will lead to final conclusions on how to best articulate these rights.
44#
發(fā)表于 2025-3-29 06:15:42 | 只看該作者
45#
發(fā)表于 2025-3-29 11:19:18 | 只看該作者
46#
發(fā)表于 2025-3-29 14:46:47 | 只看該作者
47#
發(fā)表于 2025-3-29 17:38:52 | 只看該作者
48#
發(fā)表于 2025-3-29 20:51:15 | 只看該作者
Introducing Positive Discrimination in Predictive Modelsas a latent variable. By explicitly modeling the discrimination, we can reverse engineer decisions. Since all three models can be seen as ways to introduce positive discrimination, we end the chapter with a reflection on positive discrimination.
49#
發(fā)表于 2025-3-30 00:59:45 | 只看該作者
50#
發(fā)表于 2025-3-30 06:01:29 | 只看該作者
Discrimination and Privacy in the Information SocietyData Mining and Prof
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