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

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Urban Perception: A deep learning approach Student: Jack Kenning
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 19 and 20: The presence of vegetation is not s
Page 21 and 22: Results & Discussion Results & Disc
Page 23: Conclusions The hypothesis and rese
Page 26 and 27: Motivation Street cross section des
Page 28 and 29: Figure 2 survey result As shown in
Page 30 and 31: 2. Cluster Figure 4 cluster analysi
Page 32 and 33: Secure = - 0.008 * street width + 2
Page 34 and 35: 34 New Methods in Creative Data Min
Page 36 and 37: Motivation Security Analysis Securi
Page 38 and 39: Figure 4: Decibel versus noise leve
Page 40 and 41: Figure 7: Scatter plot 2.2 Single v
Page 42 and 43: Figure 8: Single variable linear re
Page 44: Chair of Information Architecture

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

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