Data Analysis Machine Learning and Applications Episode 2 Part 10 docx

Data Analysis Machine Learning and Applications Episode 3 Part 9 docx

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.,...

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Data Analysis Machine Learning and Applications Episode 1 Part 2 potx

Data Analysis Machine Learning and Applications Episode 1 Part 2 potx

... Proc. of 26 th DAGM-Symposium. Springer, 22 0 22 7. HAASDONK, B. and BURKHARDT, H. (20 07): Invariant kernels for pattern analysis and machine learning. Machine Learning, 68, 35– 61. SCHÖLKOPF, B. and ... Networks, 12 (5), 987–997. TITSIAS, M.K. and LIKAS, A. (20 02) : Mixtures of Experts Classification Using a Hierarchi- cal Mixture Model. Neural Computation, 14 , 22 21...

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Data Analysis Machine Learning and Applications Episode 1 Part 3 docx

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...

Ngày tải lên: 05/08/2014, 21:21

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Data Analysis Machine Learning and Applications Episode 1 Part 6 docx

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...

Ngày tải lên: 05/08/2014, 21:21

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Data Analysis Machine Learning and Applications Episode 1 Part 10 ppt

Data Analysis Machine Learning and Applications Episode 1 Part 10 ppt

... 1 1 1 1 ∗ c4–g4 1 1 1 1 1 c4–a4 1 1 1 1 1 c4–c5 1 1 0 1 ∗ 1 instrument notes flu guit pian trum viol c4–c4 0 0 1 ∗ 1 ∗ 1 c4–e4 1 1 1 1 1 ∗ c4–g4 1 1 1 1 1 c4–a4 1 1 1 1 1 c4–c5 1 1 1 ∗ 1 ∗ 1 4.3 ... 1 1 1 1 1 c4–e4 0 1 0 0 1 c4–g4 0 0 0 0 0 c4–a4 1 1 1 0 0 c4–c5 1 1 1 1 1 instrument notes flu guit pian trum viol c4–c4 1...

Ngày tải lên: 05/08/2014, 21:21

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Data Analysis Machine Learning and Applications Episode 2 Part 1 pot

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...

Ngày tải lên: 05/08/2014, 21:21

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Data Analysis Machine Learning and Applications Episode 2 Part 2 ppsx

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 = [ˆu  W 2 ˆu/ ˆ V 2 ] 2 T 22 −(T 21 A ) 2 ˆvar( ˆ U) , (6) LM A U = [ˆu  B  BW 1 y] 2 H rho −H TU ˆvar( ˆ T)H  TU , (7) where T 2...

Ngày tải lên: 05/08/2014, 21:21

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Data Analysis Machine Learning and Applications Episode 2 Part 3 pps

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 (...

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Data Analysis Machine Learning and Applications Episode 2 Part 4 doc

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...

Ngày tải lên: 05/08/2014, 21:21

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Data Analysis Machine Learning and Applications Episode 2 Part 5 pps

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 0 1 2 3 4 5 6 x 10 6 0 5 1 0 1 5 2 0 2 5 0 0 .5 1 1 .5 2 2 .5 x ... 20 30 40 50 60 70 80 0 0 .2 0.4 0.6 0.8 1 Typical day 12 0 5 10 15 20 25 0 1 2 3 4 5 x 10 7 0 5 1 0 1 5 2 0 2 5 0 2 4 6 8 10 x 10 6 cluster 6, a...

Ngày tải lên: 05/08/2014, 21:21

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Data Analysis Machine Learning and Applications Episode 2 Part 6 potx

Data Analysis Machine Learning and Applications Episode 2 Part 6 potx

... 361 108 560 1 8 26 109 36 0 26 285183 18 16 923 1 021 51 1948 123 47 02 1 924 30044079003 5 26 98 1858 24 7198 924 00 1898 26 3 26 62 8 200005145 1775 22 800903 921 91 060 100 56 1 922 70 460 0 1 969 9 761 860 1847 1 8 26 18 161 9481 924 1858189817751 922 1 969 1847 108 560 1 8 26 109 36 0 26 285183 18 16 923 1 021 51 1948 123 47 02 1 924 30044079003 5 26 98 1858 24 71...

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Data Analysis Machine Learning and Applications Episode 2 Part 7 docx

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...

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Data Analysis Machine Learning and Applications Episode 2 Part 8 docx

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...

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Data Analysis Machine Learning and Applications Episode 2 Part 9 pdf

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...

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Data Analysis Machine Learning and Applications Episode 2 Part 10 docx

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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