Creative Data Mining : Documentation of the teaching results from the Spring Semester 2017

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Chair <strong>of</strong> Information Architecture
Page 1: Documentation of the teaching resul
Page 5: Course Description and Program Crea
Page 9 and 10: Objectivity, Subjectivity, Colour S
Page 11 and 12: We We did did clustering for for ea
Page 13 and 14: Creative Data Mining | Spring 2017
Page 15: Conclusions Through our three group
Page 18 and 19: mation process and ends with a visu
Page 20 and 21: In this case, the project relied la
Page 22 and 23: The The output output had had a a g
Page 25 and 26: Street Cross Section Student: Hong
Page 27 and 28: Table 1 street cross section data o
Page 29 and 30: Results & Discussion Results & Disc
Page 31 and 32: 3. Multi-variable linear regression
Page 33 and 34: From last analysis, we find the mos
Page 35 and 36: Security Analysis Student: Gong Che
Page 37 and 38: Besides, another hypothesis made in
Page 39 and 40: chaotic/ordered, noisy/quiet, borin
Page 41 and 42: Creative Data Mining | Spring 2017
Page 43: New Methods in Creative Data Mining

Creative Data Mining : Documentation of the teaching results from the Spring Semester 2017

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