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Topics include in this course are Data Warehousing Concepts, Design and Development, Extraction, Transformation and Loading, OLAP Technology, Data Mining Techniques: Classification, Clustering and Decision Tree, Advanced Topics. This lecture includes: Data, Mining, Process, Interdisciplinary, Field, Statistics, Databases, Pattern, Recognition, Visualization, Instances
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-^ “…the analysis of observational data sets to findunsuspected relationships and to summarize data innovel ways…”^ (Hand et al.)•^ “…is an interdisciplinary field bringing togethertechniques from machine learning, pattern recognition,statistics, databases, and visualization…”
- Hypothetical Training Data for Disease Diagnosis Table 1.1 (^) Patient Sore^ SwollenID# Throat^ Fever^ Glands Congestion^ Headache^ Diagnosis 1 Yes Yes Yes Yes^ Yes^ Strep throat 2 No No No Yes^ Yes^ Allergy 3 Yes Yes No Yes^ No^ Cold 4 Yes No Yes No^ No^ Strep throat 5 No Yes No Yes^ No^ Cold 6 No No No Yes^ No^ Allergy 7 No No Yes No^ No^ Strep throat 8 Yes No No Yes^ Yes^ Allergy 9 No Yes No Yes^ Yes^ Cold 10 Yes^ Yes^ No^
Yes^ Yes^ Cold
- Data Instances with an Unknown Classification Table 1.2 (^) Patient^ Sore^ SwollenID# Throat Fever Glands^ Congestion^ Headache^ Diagnosis 11 No No Yes^ Yes^ Yes^
12 Yes^ Yes^ No^
No^ Yes^? 13 No^ No^ No^
No^ Yes^?
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