Functional MRI data analysis detection, estimation and modelling
Functional MRI data analysis detection, estimation and modelling
... design and the other is an event-related design; we will refer to these two data sets respectively as DATA- BLOCK and DATA- EVENT, hereafter These data sets are obtained from the National fMRI data ... etc.) and the measurement settings (including environment, BOLD effect, data acquisition, spatial reconstruction, artifacts, preprocessing etc.) Since fMRI data is a 4-D data...
Ngày tải lên: 13/09/2015, 20:30
Data Analysis Machine Learning and Applications Episode 3 Part 9 docx
... Thiel, Klaus, 4 79 Mair, Patrick, 5 93 Manni, Franz, 645 March, Nicolas, 4 39 Marinho, Leandro B., 533 Mehler, Alexander, 6 53 Meinl, Thorsten, 31 9 Meißner, Martin, 447 Merkel, Andreas, 5 53 Messaoud, ... Martin, 39 7 Schiffner, Julia, 69 Schliep, Alexander, 1 19 Schmidt-Thieme, Lars, 171, 525, 533 Scholz, Sören W., 447 Schröder, Jan, 35 5 Schulz, Sascha, 39 7 Schwaiger, Manfred,...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 1 Part 1 doc
... 10 9 10 8 13 4 12 6 13 0 14 0 13 8 17 9 16 6 14 41 0.7 15 3 200 19 8 16 8 17 7 16 0 17 3 17 2 18 5 18 7 17 39 22 18 10 7 12 7 12 9 16 2 54 55 71 1 31 116 15 0 10 3 10 4 14 7 14 6 14 9 11 9 10 5 61 62 14 4 12 2 10 1 11 7 13 3 11 1 ... 15 4 18 0 200 17 5 17 8 17 6 19 9 15 0 12 4 77 0.6 15 3 17 4 18 6 15 1 14 8 12 0 14 3 10 8 11 4 13 5...
Ngày tải lên: 05/08/2014, 21:21
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 SMOLA, ... Networks, 12 (5), 987–997 TITSIAS, M K and LIKAS, A (20 02) : Mixtures of Experts Classification Using a Hierarchical Mixture Model Neural Computation, 14 , 22 21 22 44...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 1 Part 3 docx
... Classification Time 03 : 13 .60 00 :14 . 73 00 :14 . 63 Classif Accuracy % 95.78 % 91. 01 % 91. 01 % USPS (Min-Max) RBF Kernel 17 5 51. 5 5 51. 5 1. 37 13 .14 1. 05 1. 04 13 . 23 1. 05 H1-SVM H1-SVM RBF/H1 RBF/H1 Gr-Heu Gr-Heu ... taken 200 200 18 0 18 0 16 0 16 0 14 0 14 0 12 0 12 0 10 0 10 0 80 80 60 60 40 40 20 20 20 40 60 80 10 0 12 0 14 0 16 0 18 0 200 20 40 6...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 1 Part 4 pptx
... 0.978 81 0.39823 1. 00000 0. 616 15 0.99 843 0.62620 1. 00000 0. 542 75 1. 00000 0.9 94 41 0.53337 96 .44 % 0.03 313 0 . 14 44 0 median 0.0 210 7 0.85 840 0.00088 0.99062 0.0 017 7 1. 00000 0. 342 31 0.90252 0 .18 1 94 0. 844 63 ... 0.53576 0.90705 0. 340 71 0.60606 0 .44 997 0.872 24 0.6 013 9 0. 848 88 0.608 21 0.8 718 3 0 .11 946 0.87399 0 .4 318 0 0.96372 0 .45 915 0.9 849 8...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 1 Part 5 pdf
... COPK-Means ssALife with U*C 71 65. 7 10 0 96.4 55 .2 10 0 10 0 93.4 90 10 0 10 0 10 0 10 0 10 0 10 0 10 0 10 0 96.3 Fig Density defined clustering problem EngyTime: (a) partially labeled data (b) ssALife produced ... 0.626 0. 314 0 .56 6 0. 050 0 .11 2 0.062 0.680 0.600 15 1 = classes for the 0. 912 0. 452 0.366 0. 658 0.088 0.944 0.872 0.930 0. 310 0.390 0.006 0.060 0.008 0.02...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 1 Part 6 docx
... repeat (c1 , c2 ) ← 10 : 11 : 12 : 13 : argmax c1 ,c2 ∈P∧(c1 ×c2 )∩Rcl = sim(c1 , c2 ) if sim(c1 , c2 ) ≥ then P ← (P \ {c1 , c2 }) ∪ {c1 ∪ c2 } end if until sim(c1 , c2 ) < 14 : return P 15 : end procedure ... Name) (x1 , x2 ) (x1 , x3 ) (x2 , x3 ) (Product Name) 0 .6 0 .1 0.0 0 0.0 76 0.849 0. 860 Feature Vector P[xi ≡ x j ] (0 .6, 1, 0.0 76) (0 .1, 0, 0.849) (0.0, 0, 0. 860 ) 0.8...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 1 Part 7 doc
... follows: (t +1) (t +1) K |··· ∼ W 1( t +1) |··· k ∼ N (nk ⎛ , k =1 | · · · ∼ D( + n1 , , + nK ), (t +1) |··· k (t) 1 1 ) k + 2g , (2h + (t) 1 k + ) 1 (nk ∼ W ⎝2 + nk , (2 (t +1) (t) 1 yk + k + i:zi ... 363– 375 11 8 Marco Di Zio and Ugo Guarnera DI ZIO, M., GUARNERA, U and LUZI, O (20 07) : Imputation through finite Gaussian mixture models Computational Statistics and Data Anal...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 1 Part 8 ppsx
... Kerf1 =1 Tie =1 Walle=3 Pin=3 Black=2 Walle=2 Kerf2 =1 Pin =1 Hat =1 Keyri =1 Sculp =1 Umbre =1 Trays =1 Fem-T =1 Light =1 MetWa =1 Cap =1 Trayp=3 Silve=3 Hat=3 Trays=3 Umbre=3 Factor - 14 .13 % Tie=3 SkinW =1 ... Application 18 9 umbh Umbrella Hat Tie Kerchief1 Kerchief2 T shirt T shirt V Sweater Cap Trayplas Trayleather Backpack Bag Cup 0.75 0.90 0.72 0 .88 0. 91 0 .85 0 .8...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 1 Part 9 doc
... Ncube, 19 85; Lowry et al., 19 92 ; Jackson, 19 91 ; Liu, 19 95 ; Kourti and MacGregor, 19 96 , MacGregor, 19 97 ) In particular, we focus on the approach based on PLS components proposed by Kourti and MacGregor ... In particular, the bootstrap approach to estimate control 202 Rosaria Lombardo, Amalia Vanacore and Jean-Francçois Durand limits (Wu and Wang, 19 97 ; Jones a...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 1 Part 10 ppt
... viol c4–c4 c4–e4 c4–g4 c4–a4 c4–c5 1 1 1 1 1 1 1∗ 1 1∗ 1 1 instrument notes flu guit pian trum viol c4–c4 c4–e4 c4–g4 c4–a4 c4–c5 1 1 1 1 1 1 1∗ 1 1 1∗ 1 1 4.3 Results with extended polyphonic ... 68,50 75 ,10 tion Optimality 97,40 96,60 96 ,10 96 ,10 96 ,10 81, 90 90,40 91, 00 90,50 Note: TCCS, POLCOURT and SCSCIENCE stand for “Teacher, Clerck and Civil Servan...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 2 Part 1 pot
... watermark database Table Averaged precision and recall at N /2 for the watermark database Classes 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 92 243 21 4 14 4 10 9 24 4 17 3 ... 600 -400 log likelihood -20 0 27 5 -800 -10 00 - 12 0 0 10 0 passing aborted passing follow -14 00 -16 00 20 0 10 -10 0 15 20 25 30 time (s) -20 0 passing...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 2 Part 2 ppsx
... al 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) ... Intelligent Data Analysis, 6(3) :23 7 25 5 KAM, P.-S and FU, A W.-C (20 00): Discovering Temporal Patterns for Interval-Based Events In: Data Warehousing and...
Ngày tải lên: 05/08/2014, 21:21
Data Analysis Machine Learning and Applications Episode 2 Part 3 pps
... WESTERHEIDE 20 0001 BESTEWEIDE 20 00 02 WESTERWELLE asoundex.lname W 236 B 233 W 236 3. 3 Candidate selection candidates (data1 , data2 , method, selvars1, selvars2, key1, key2, ) provides an interface ... [%] W2W2, =0.5 0.7 0.6 0.5 0.4 0 .3 0 .2 0.7 W1W1, =0.5 0.6 W W , =0.5 0.5 W2W2, =0.5 0.4 W W , =0.5 2 0 .3 0 .2 0.1 W2W2, =0.5 0 .2 W1W1, =0.5 0.5 0.4 W W , =0.5 power 30 7 0....
Ngày tải lên: 05/08/2014, 21:21
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