Data Analysis Machine Learning and Applications Episode 2 Part 4 doc
Data Analysis Machine Learning and Applications Episode 3 Part 9 docx
... R., 31 9
Bessler, Wolfgang, 499
Biemann, Chris, 577
Borgelt, Christian, 2 29
Bradley, Patrick E., 95
Brunner, Gerd, 237
Brusch, Michael, 431
Burgard, Wolfram, 2 69, 2 93
Burkhardt, Hans, 11, 37 , 237
Calò, ... Wendelin, 2 69
Fernández-Aguirre, K., 1 83
Fessant, F., 34 3
Fiedler, Mathias, 2 29
Flodman, Pamela, 1 19
Franke, Markus, 35 5
Fried, Roland, 277
Gabriel, Thomas R.,...
Data Analysis Machine Learning and Applications Episode 1 Part 1 doc
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Data Analysis Machine Learning and Applications Episode 1 Part 3 docx
... 14 :55. 23 10 :55.70 14 : 21. 99 1. 37 1. 04
Classification Time 03 : 13 .60 00 :14 . 73 00 :14 . 63 13 .14 13 . 23
Classif. Accuracy % 95.78 % 91. 01 % 91. 01 % 1. 05 1. 05
USPS RBF H1-SVM H1-SVM RBF/H1 RBF/H1
(Min-Max) Kernel ... 2.62 3. 87 77 .30 46.67
2 28. 83 88. 41 18.06 2.50
1 68.54 7.44 2.54 0.00
SRNG 1 2 3 4
4 0.00 0.56 2.08 53. 33
3 0.67 3. 60 81. 12 44 .1...
Data Analysis Machine Learning and Applications Episode 1 Part 4 pptx
... 0.89 642 0.763 84 0. 712 12 0.85838
¯r 0.5 313 0 0 .4 41 1 9 0.56066 0 .44 540 0 .45 403 0.39900 0. 618 83 0. 747 30
ccr 98.22% 98.00% 94. 44% 90.67% 97 .11 % 89.56% 98.89% 98 .44 %
11 a 0. 043 35 0. 043 94 0.00 012 0. 043 88 ... 0. 547 46 0.6 013 9 0.27 610 0 .46 735 0.58050 0 .49 842 0.33303 0.5 017 8
b 0. 910 71 0. 848 88 0 .48 550 0.73720 0. 813 17 0.79 644 0.72899 0. 744 62
6
a 0. 6...
Data Analysis Machine Learning and Applications Episode 1 Part 6 docx
... data.
grandfather 0.000 0.024 0. 012
0. 965 0.000
grandmother 0.005 0 .13 4 0. 0 16
0.840 0.005
granddaughter 0 .11 3 0.242 0.054
0. 466 0 .12 5
grandson 0 .13 4 0 .11 1 0.052
0.5 81 0 .12 2
brother
0. 61 2 0.282 0.024 0.082 ... 0.000
sister
0.579 0.3 91 0.0 26 0.002 0.002
father 0.099
0.5 46 0 .12 2 0 .15 8 0.075
mother 0.089
0 .65 4 0 .13 6 0.054 0. 066
daughter 0.000
1. 000 0.0...
Data Analysis Machine Learning and Applications Episode 2 Part 1 pot
... watermark database.
Table 1.
Averaged precision and recall at N /2 for the watermark database.
Classes 1 2 3 4 5 6 7 8 9 10 11 12 13 14
N 322 11 5 13 9 71 91 44 19 7 12 6 99 33 14 31 17 416
P(N /2) .4 92 .24 3 ... 416
P(N /2) .4 92 .24 3 . 21 4 .14 4 .10 9 .24 4 .17 3 .097 .4 42 .068 .19 0 .8 02 .556 .28 3
R(N /2) . 528 .13 9 .3 02 .19 7 .088 .1 82 .1 52 .19 1...
Data Analysis Machine Learning and Applications Episode 2 Part 2 ppsx
... 20 01), FSG (Kuramochi and Karypis 20 01),
MoSS/MoFa (Borgelt and Berthold 20 02) , gSpan (Yan and Han 20 02) , Closegraph
(Yan and Han 20 03), FFSM (Huan et al. 20 03), and Gaston (Nijssen and Kok 20 04).
A ... (1988b):
LM
A
O
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W
2
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ˆ
V
2
]
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ˆvar(
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1
y]
2
H
rho
−H
TU
ˆvar(
ˆ
T)H
TU
, (7)
where T
2...
Data Analysis Machine Learning and Applications Episode 2 Part 3 pps
... preparation (data= d1, variable='lname',
method='asoundex')
lname asoundex.lname
11 525 6 WESTERHEIDE W 236
20 0001 BESTEWEIDE B 233
20 00 02 WESTERWELLE W 236
3. 3 Candidate selection
candidates (data1 , ... retains only 83
candidates.
> candidates (data1 =d1.prep, data2 =d2.prep,
method='blocking',selvars1='asoundex.lname')
> candidates (...
Data Analysis Machine Learning and Applications Episode 2 Part 4 doc
... winners).
Misclassification
J4.8 J4.8(cv) RPart0 RPart1 QUEST CTree
J4.8 029 911839
J4.8(cv)
40 8911 941
RPart0
560710735
RPart1
641 08 625
QUEST
42 2 50 720
CTree
76789037
26 20 27 38 49 37
Complexity J4.8 J4.8(cv) RPart0 ... RPart0 RPart1 QUEST CTree
J4.8 010 020 3
J4.8(cv)
17 0 0 0 5 3 25
RPart0
18 18 0 0 13 15 64
RPart1
18 18 16 0 14 15 81
QUEST
15 13 5 4 0 10 47
CT...
Data Analysis Machine Learning and Applications Episode 2 Part 5 pps
... (4 .5% )
Global mean
typical application day cluster number
unknown
up
unknown
down
p2p
up
p2p
down
web
up
web
down
0 5 10 15 20 25
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0
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0.6
0.8
1
Typical day 12
0 5 10 15 20 25
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3
4
5
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7
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1
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5
2
0
2
5
0
2
4
6
8
10
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6
cluster 6, a...
Data Analysis Machine Learning and Applications Episode 2 Part 6 potx
... 361
108 560
1 8 26
109 36 0 26 285183
18 16
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1948
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24 71...
Data Analysis Machine Learning and Applications Episode 2 Part 7 docx
... Identification. Socimetry, 28 ,
27 7 29 9.
OKADA, A. (20 03): Using Additive Conjoint Measurement in Analysis of Social Network
Data. In: M. Schwaiger, and O. Opitz (Eds.): Exploratory Data Analysis in Empirical
Research. ... 2
Characteristic values
Actor (Family) 4 .23 3 3.418
1 Acciaiuoli 0. 129 0.134
2 Albizzi 0 .21 0 0.300
3 Barbadori 0. 179 0.053
4 Bischeri 0. 328 -0 .26...
Data Analysis Machine Learning and Applications Episode 2 Part 8 docx
... 7. 78 24 (2) .24 (1) 12. 84 32 (2) . 32 (1)
Type of building 9.09 . 08 (2) 22 (3) 8. 36 03 (2) 12 (3)
.14 (1) .15 (1)
Outside facilities 7.40 .25 (1) .00 (2) 12. 11 . 28 (1) 09 (2)
25 (3) 19 (3)
(* The ... (1)
37 (3) 26 (3)
Beach 9 .83 10 (2) .35 (1) 5.56 09 (2) .26 (1)
25 (3) 17 (3)
Hotel services
Leisure activities 11. 72 20 (6) 02 (2) 7. 52 04 (6) . 02 (2)
.04 (2) .20...
Data Analysis Machine Learning and Applications Episode 2 Part 9 pdf
... pseudo R
2
1 -131. 49 28 0 .97 28 9. 97 .00 .23
2 -117.04 27 6. 09 29 7. 09 . 09 .81
3 -100 .96 26 7. 92 300. 92 .08 . 92
4 - 89. 76 26 9. 52 314. 52 .11 . 92
5 - 82. 62 2 79 .24 336 .24 .11 .95
Classifying Contemporary ... biased
T
04s
8 .93 2. 10 2. 59 biased
T
05s
10. 59 -8.75 -4.70 biased
TM score 3.67 4.05 .88 10 . 29
DM score 2. 71 1.03 -7.87 8 .94
EM...
Data Analysis Machine Learning and Applications Episode 2 Part 10 docx
... ’000)
20 00 20 01 20 02 2003 20 04
0
25
50
75
100
125
150
Box Jenkins (# 10)
SE (in ’000)
20 00 20 01 20 02 2003 20 04
0
25
50
75
100
125
150
Linear Regression (# 2)
SE (in ’000)
20 00 20 01 20 02 2003 20 04
0
25
50
75
100
125
150
VAR(4)-Model ... 0.00.51.01. 52. 02. 53.0
ARL 3 42. 18 341. 42 339. 42 334. 52 326 .63 316.80 306. 92
SDRL 338.74 338. 62...
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