Data Analysis Machine Learning and Applications Episode 3 Part 2 pdf

... R., 31 9 Bessler, Wolfgang, 499 Biemann, Chris, 577Borgelt, 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 3Fiedler, Mathias, 2 29 Flodman, Pamela, 1 19 Franke, Markus, 35 5Fried, Roland, 277Gabriel, Thomas R., 31 9 Gallo, Michele, 1 93 Gangi, Francesco, ... 127Herrmann, Lutz, 1 39 Hipp, Jochen, 2 53 Holm, Hans J., 6 29 Hornik, Kurt, 147, 38 9, 5 69 Hoser, Bettina, 35 5Hrycej, Tomas, 405Hudec, Marcus, 5 93 Iglesias-Rozas, José R, 55Irpino, Antonio, 7 03 Joaquin...

... able2 14 4423284446224389 11 20 16 15 6 21 50 13 302749 1 5292834735223 31 3748 12 2639 10 45 17 23257598 18 433633 19 47907082 71 41 40577894845888795955 51 91 738564 61 65628096898395 10 06354749253728776939766 81 696799 11 3688656607752 13 9 13 4 13 0 10 3 13 8 10 9 14 0 14 3 11 4 12 4 13 7 12 7 12 6 13 3 10 7 10 4 13 1 14 6 10 8 13 5 14 4 11 1 11 7 13 6 10 5 14 2 13 2 11 5 12 1 14 7 15 0 10 1 14 5 11 0 12 2 12 5 10 2 14 1 10 6 14 8 12 0 11 6 11 9 12 9 12 8 15 5 11 2 11 8 12 3 14 9 17 2 17 7 16 9 16 7 15 9 17 8 16 4 19 8 16 0 15 7 18 4 16 3 17 6 19 9 17 1 18 2 16 2 19 5 15 8 19 6 15 2 17 0 18 1 16 6 18 9 15 3 18 6 17 5 19 7 19 0 17 9 19 2 15 6 16 5 19 1 18 5 18 8 19 4 17 4 15 1 15 4 18 0200 16 8 17 3 18 7 16 1 19 3 18 3n00 .1 0.20.30.40.50.60.70.80.9 1 (b)Fig. ... able1 14 4423284446224389 11 20 16 15 6 21 50 13 302749 1 5292834735223 31 3748 12 2639 10 45 17 23257598 18 433633 19 47907082 71 41 40577894845888795955 51 91 738564 61 65628096898395 10 06354749253728776939766 81 696799 11 3688656607752 13 9 13 4 13 0 10 3 13 8 10 9 14 0 14 3 11 4 12 4 13 7 12 7 12 6 13 3 10 7 10 4 13 1 14 6 10 8 13 5 14 4 11 1 11 7 13 6 10 5 14 2 13 2 11 5 12 1 14 7 15 0 10 1 14 5 11 0 12 2 12 5 10 2 14 1 10 6 14 8 12 0 11 6 11 9 12 9 12 8 15 5 11 2 11 8 12 3 14 9 17 2 17 7 16 9 16 7 15 9 17 8 16 4 19 8 16 0 15 7 18 4 16 3 17 6 19 9 17 1 18 2 16 2 19 5 15 8 19 6 15 2 17 0 18 1 16 6 18 9 15 3 18 6 17 5 19 7 19 0 17 9 19 2 15 6 16 5 19 1 18 5 18 8 19 4 17 4 15 1 15 4 18 0200 16 8 17 3 18 7 16 1 19 3 18 3n00. ... able12435 18 41 62633830 61 54 10 07660996255 71 22 14 27 12 204677926463897378 17 39 16 11 21 35044678666598532344938 31 9795986587885393562836 19 10 45525968490 1 42294474879 51 57 81 91 759440 15 7 11 27468828369728029374352 19 2 13 23 11 4 11 0 11 5 17 0 15 65870 15 2 19 0 11 1 14 8 12 8 15 9 15 1 16 9 18 4 18 6 12 4 10 6 11 7 13 3 11 9 10 2 14 2 12 3 14 1 19 4 15 5 17 8 12 0 13 6 10 5 11 8 16 2 16 7 19 6 17 2 18 7 16 5 15 7 16 4 10 4 14 6 11 3 13 5 12 7 15 3 19 8 16 8 17 3 18 5 16 3 18 8 17 6 18 3 19 5 17 1 14 4 13 1 15 0 10 3 14 7 14 9 12 9 17 5 19 3200 17 7 18 2 12 2 11 6 10 7 12 6 13 0 13 8 16 0 17 9 18 9 15 4 10 1 10 8 14 0 19 7 16 6 17 4 12 5 14 5 12 1 13 7 14 3 10 9 13 4 13 2 13 9 15 8 19 9 18 1 16 1 19 1 18 0n0 .1 0.20.30.40.50.60.70.80.9(a)Vari...

... 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 22 44.TUTZ, G. and BINDER H. (20 05): ... 0. 619 P 1 v–rest,no0.973 0. 618 0.803 0.646 0.9 81 0.588P 1 v–rest,map0.973 0.9 42 0.803 0.785 0.978 0.9 21 P 1 v–rest,assign0.973 0.896 0.796 0.7 52 0.976 0. 829 P 1 v–rest,Dirichlet0.973 0.963 0. 815 ...

... 14 :55. 23 10 :55.70 14 : 21. 99 1. 37 1. 04Classification 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. 05USPS RBF H1-SVM H1-SVM RBF/H1 RBF/H1(Min-Max) Kernel ... 2.62 3. 87 77 .30 46.672 28. 83 88. 41 18.06 2.50 1 68.54 7.44 2.54 0.00SRNG 1 2 3 44 0.00 0.56 2.08 53. 33 3 0.67 3. 60 81. 12 44 .17 2 28. 21 85 .35 15 .54 2.50 1 71. 12 10 .50 1. 25 0.00SVM 1 2 3 4Total ... grade 1 tumors were classified as grade 3 in 2.26%of the cases.4 0.00 0.00 4.20 48 .33 3 1. 92 8. 31 70 .18 49 .17 2 26. 83 79.80 22.26 0.00 1 71. 25 11 .89 3. 35 2.50LVQ 1 2 3 44 0.00 0.28 2 .10 50. 83 3...

... 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 30ccr 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 8b 0. 910 71 0. 848 88 0 .48 550 0.73720 0. 813 17 0.79 644 0.72899 0. 744 626a 0. 610 74 0.608 21 0 .13 40 0 0.53296 0. 610 37 0.5 642 6 0.3 511 3 0 .47 885b ... 0.85 946 0.60606 0.3 612 1 0. 610 90 0.68223 0. 5 14 87 0 .4 919 9 0. 611 56 4 a 0.35609 0 .44 997 0.0 012 7 0 .43 860 0.53509 0 .47 083 0. 046 77 0.00295b 0.83993 0.872 24 0.56 313 0.565 41 0.8 0 14 9 0.6 210 2 0.5 41 0 9 0.8 015 65a...

... dendrogramsQ20 1 3 4 12 20 32 640 f 0022 256 1 0 f 10 0000301f 00 0004200f 3422 12 2003f 322202004 3 f 21 32 50 02 2 2 f 5 646002 2 1 5 fFig. 1. 2-adic valuations for D.0 1 0 1 0 1 20 1 30 1 40 1 5 0 1 60 1 06432420 12 ... random initialization data set COPK-Means ssALife with U*CAtom 71 100Chainlink 65. 7 10 0Hepta 10 0 10 0Lsun 96.4 10 0Target 55 .2 10 0Tetra 10 0 10 0TwoDiamonds 10 0 10 0Wingnut 93.4 10 0EngyTime 90 ... ensembleGordon and Vichi (20 01, Table 1) provide soft partitions of 21 countries based onmacroeconomic data for the years 19 75, 19 80, 19 85, 19 90, and 19 95. These parti-tions were obtained using fuzzy c-means...

... data. grandfather 0.000 0.024 0. 012 0. 965 0.000grandmother 0.005 0 .13 4 0. 0 16 0.840 0.005granddaughter 0 .11 3 0.242 0.0540. 466 0 .12 5grandson 0 .13 4 0 .11 1 0.0520.5 81 0 .12 2brother0. 61 2 0.282 0.024 0.082 ... 0.000sister0.579 0.3 91 0.0 26 0.002 0.002father 0.0990.5 46 0 .12 2 0 .15 8 0.075mother 0.0890 .65 4 0 .13 6 0.054 0. 066 daughter 0.000 1. 000 0.000 0.000 0.000son 0.0 31 0.842 0.007 0 .11 3 0.007nephew 0. 012 0.047 ... Name) (Product Name) (Price)(x 1 ,x2) 0 .6 1 0.0 76 (0 .6, 1, 0.0 76) 0.8(x 1 ,x3) 0 .1 0 0.849 (0 .1, 0, 0.849) 0.2(x2,x3) 0.0 0 0. 860 (0.0, 0, 0. 860 ) 0 .1 4 .1 Collective decision model with...

... 1 035 11 4 15 9 13 17 158 0 . 31 4Polynomial(3rd degree) 12 42 633 516 14 767 17 158 0.6 43 RBF860 6 51 498 15 149 17 158 0.640Coulomb0 11 24 25 16 009 17 158 0 .14 8M1287 850 299 15 722 17 158 0.505M2* 19 1 ... MeNonV BT3Ratios VBT2NonV BT2VBT3NonV BT3Test1 Test2ROS 9.52 3. 93 5 .39 2 .16 1 03 11 6ROE 6.7 3. 83 3 .3 2. 01 111 11 0ROI 6.85 3. 83 -1. 51 1.5 1 13 10 5Leverage 79.75 72.52 226.96 88.28 12 0 58**governance ... 0.505M2* 19 1 33 1 256 12 425 13 2 03 0.655M3** 35 48 33 1 818 12 425 17 158 0.7 43 * 39 55 credit clients could not be classified.**Default classbadfor 39 55 credit clients. and by w = 11 49 32 3forbadcredit...

... Artificial Intelligence, pp. 43 52, July 1998.BURKE, R. (20 02) : Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction. vol. 12( 4), pp. 33 1 37 0.HERLOCKER, J.L., ... EachMovie, containing 2, 558,871votes from 61, 1 32 users on 1,6 23 movies, and the MovieLens100k dataset, contain-ing 100,000 ratings from 9 43 users on 1,6 82 movies. The datasets also contain ... and development in information retrieval. New York,NY, USA: ACM Press, 20 02, pp. 2 53 26 0.TSO, K. and SCHMIDT-THIEME L. (20 05): Attribute-aware Collaborative Filtering. In Pro-ceedings of 29 th...

... WeibullK=2 K =3 K=4 K=5separate 233 39.27 232 02. 23 230 40.01 229 43. 11main.g 233 55.66 230 58.25 22971.86 228 63. 43 main.p 235 03. 73 233 68.77 231 65.60 230 68.47int.gp 235 72.21 234 22.51 233 05. 63 230 75.76main.gp ... 1285 4 4 4 120 120 126 3 2 15 10 13 105 108 107 32 322229497 93 436 30297479795414 233 676564±10 234 3 231 787075 35 9 535 445514248564672 435 195906768182614 30 2595447 433 945 38 4666522252149586651614115 ... jewelleryComponent1 1 .36 234 2 2.981528 1.116042 0.7 935 599 0.91454 63 Component2 1 .36 234 2 2.981528 1.116042 0.7 935 599 0.91454 63 Component3 1 .36 234 2 2.981528 1.116042 0.7 935 599 0.91454 63 Component4 1 .36 234 2 2.981528...

... Equation 3 and Figure 4: Pnìm= UnìcÃScìcÃVcìm (3) 2.69 0.57 2.22 4. 250.78 3. 93 2.21 0. 04 3. 17 1 .38 2.92 4. 78Pnìi-0.61 0.28-0.29 -0.95-0. 74 0. 14 Unìc8.87 00 4. 01Scìc-0 .47 -0.28 ... efc(0.17)Portal 1 0.1126 0.20 54 0.2815 0 .35 18 0. 640 8 0.7685 0 .36 Portal 2 0. 142 5 0.2050 0.1 836 0.2079 0.1965 0. 233 8 0.18Portal 3 0.0058 0. 245 5 0.02 54 0. 245 9 0 .33 82 0 .41 75 0.15Fig. 2. Decision matrix ... f1does.f1f2f 3 f 4 U1 4 1 1 4 U21 4 2 0U 3 2 1 4 5(a)f1f2f 3 f 4 U 4 1 4 1 0(b)Fig. 2. User-Feature matrix P divided in (a) Training Set (nìm), (b) Test Set 3. 2 Applying SVD on training data Initially,...

... weight-ings.Rand cRandktf tf-idf tf tf-idf 3 0.48 0.49 0. 03 0. 03 40 .51 0 .52 0. 03 0. 03 5 0 .54 0. 53 0.02 0.0260 .55 0 .56 0.02 0. 03 Average 0 .52 0 .52 0.02 0. 03 ments are rather low, indicating that ... the percentage identified by humans.Senate size 03 59 Documents 0 255 739 0Percentage0.000 25. 654 74 .34 6 0.000Human Percentage2.116 27 .30 6 70 .55 1 0.027Jurisdictions of the Austrian supreme ... shifts:ã shift 0: Extrablatt 0 T1 15 O 53 1 T2 15 house Hauptstr 2 T64street Heidelberg 3 T 15 city 69117 4 T2 15 zipã shift 1: 1 -1:Extrablatt -1:T1 15 0: 53 0:T2 15 1:Hauptstr 1:T64house Projecting...

... storyThe empirical tests on the data from the 66 texts support our hypothesis with good and very good 2 values. Figures 2 and 3 show typical graphs of the theoretical and empirical distributions ... information. Figure 6 shows the relationshipbetween the parameters b and c. Quantitative Text Analysis Using L-, F- and T-Segments 63 9 Table 1. Text numbers in the corpus with respect to genre and authorBrentano ... determinationcoefficient R2, which was above 0.99 in all 66 cases. The parameters b and c of the Distribution of Data in Word Lists 63 1 separation in the past. And again any mathematician has the solution:...

... Measurements and the corresponding ranks of MnOValue 0.01 0.02 0. 03 0.04 0.05 0.06 0. 07 0.08 0.09 0.10 0.11 0. 13 Frequency 171 82 071 54 231 11Rank 9 26.5 45.5 59 63 66 70 .5 73 . 5 76 78 79 80Transformation ... <T1– 07& gt;-0 .70 7-Geographic treatment <T1– 070 7> 7- North America <na4r7span:T1– 070 1-T1– 070 9:T2 7& gt; 73 United States <na4r7span:T1– 070 1-T1– 070 9:T2– 73 & gt;The information given in angle ... our DDC analysis diagram for the 37 th molecular DDC notationof his sample:Liu (19 93) , pp. 99–100 72 0 .70 73 has been decomposed as follows: 72 0: Architecture 070 7: Geographical treatment 73 : United...

... Linguistics, 637 , 655Question Answering, 5 53 R, 33 5, 38 9, 569Rank Data, 681 Recommender Systems, 525, 533 , 541,619Record Linkage, 33 5Reference Modelling, 37 3Regression, 36 3Relationships, 36 3, 629Return ... Segmentation, 479 Data Analysis, 31 9 Data Augmentation, 111 Data Depth, 455 Data Integration, 33 5 Data Mining, 421 Data Quality, 33 5 Data Transformation, 681 Decision Trees, 38 9Dendrograms, 95Design ... Machines, 3, 11, 55,77, 245, 515Supreme Administrative Court, 569Survival Analysis, 5 93 Swarm Intelligence, 139 Tagged Data, 6 73 Taxonomies, 37 3Temporal Data Mining, 2 53 Text Analysis, 637 Text...