-
1
-
-
12144251726
-
High-dimensional labeled data analysis with topology representing graphs
-
Aupetit M, Catz T (2005) High-dimensional labeled data analysis with topology representing graphs. Neurocomputing 63:139–169
-
(2005)
Neurocomputing
, vol.63
, pp. 139-169
-
-
Aupetit, M.1
Catz, T.2
-
2
-
-
0034296402
-
Generalized discriminant analysis using a kernel approach
-
Baudat G, Anouar F (2000) Generalized discriminant analysis using a kernel approach. Neural Comput 12:2385–2404
-
(2000)
Neural Comput
, vol.12
, pp. 2385-2404
-
-
Baudat, G.1
Anouar, F.2
-
3
-
-
84861139710
-
A general framework for dimensionality reducing data visualization mapping
-
Bunte K, Biehl M, Hammer B (2012) A general framework for dimensionality reducing data visualization mapping. Neural Comput 24(3):771–804
-
(2012)
Neural Comput
, vol.24
, Issue.3
, pp. 771-804
-
-
Bunte, K.1
Biehl, M.2
Hammer, B.3
-
4
-
-
84855962168
-
Limited rank matrix learning, discriminative dimension reduction and visualization
-
Bunte K, Schneider P, Hammer B, Schleif F-M, Villmann T, Biehl M (2012) Limited rank matrix learning, discriminative dimension reduction and visualization. Neural Netw 26:159–173
-
(2012)
Neural Netw
, vol.26
, pp. 159-173
-
-
Bunte, K.1
Schneider, P.2
Hammer, B.3
Schleif, F.-M.4
Villmann, T.5
Biehl, M.6
-
5
-
-
50149121547
-
-
Caragea D, Cook D, Wickham H, Honavar V. Visual methods for examining svm classifiers. In: Simoff et al (2008) Visual data mining: theory, techniques and tools for visual analytics. (Lecture Notes in Computer Science), vol 4404. Springer, pp 136–153
-
Caragea D, Cook D, Wickham H, Honavar V. Visual methods for examining svm classifiers. In: Simoff et al (2008) Visual data mining: theory, techniques and tools for visual analytics. (Lecture Notes in Computer Science), vol 4404. Springer, pp 136–153
-
-
-
-
7
-
-
35048898751
-
Informed projections
-
Becker S, Thrun S, Obermayer K, (eds), MIT Press, Cambridge
-
Cohn D (2003) Informed projections. In: Becker S, Thrun S, Obermayer K (eds) NIPS. MIT Press, Cambridge, pp 849–856
-
(2003)
NIPS
, pp. 849-856
-
-
Cohn, D.1
-
8
-
-
0037191702
-
Class visualization of high-dimensional data with applications
-
Dhillon IS, Modha DS, Spangler WS (2002) Class visualization of high-dimensional data with applications. Comput Stat Data Anal 41(1):59–90
-
(2002)
Comput Stat Data Anal
, vol.41
, Issue.1
, pp. 59-90
-
-
Dhillon, I.S.1
Modha, D.S.2
Spangler, W.S.3
-
9
-
-
84872945545
-
-
dos Santos Amorim EP, Brazil EV, II JD, Joia P, Nonato LG, Sousa MC (2012) ilamp: exploring high-dimensional spacing through backward multidimensional projection. In: IEEE VAST, IEEE Computer Society, pp 53–62
-
dos Santos Amorim EP, Brazil EV, II JD, Joia P, Nonato LG, Sousa MC (2012) ilamp: exploring high-dimensional spacing through backward multidimensional projection. In: IEEE VAST, IEEE Computer Society, pp 53–62
-
-
-
-
10
-
-
84937643115
-
-
Frank A, Asuncion A (2010) UCI machine learning repository. Accessed 1 July 2012
-
Frank A, Asuncion A (2010) UCI machine learning repository. http://archive.ics.uci.edu/ml. Accessed 1 July 2012
-
-
-
-
11
-
-
84937637784
-
-
Gisbrecht A, Hammer B Data visualization by nonlinear dimensionality reduction. WIREs Data Min Knowl Discov
-
Gisbrecht A, Hammer B Data visualization by nonlinear dimensionality reduction. WIREs Data Min Knowl Discov
-
-
-
-
12
-
-
84868020477
-
Discriminative dimensionality reduction mappings
-
IDA (Lecture Notes in Computer Science): Springer
-
Gisbrecht A, Hofmann D, Hammer B (2012) Discriminative dimensionality reduction mappings. In: Hollmén J, Klawonn F, Tucker A (eds) IDA (Lecture Notes in Computer Science), Springer, pp 126–138
-
(2012)
Hollmén J
, pp. 126-138
-
-
Gisbrecht, A.1
Hofmann, D.2
Hammer, B.3
Klawonn, F.4
Tucker, A.5
-
14
-
-
33745887620
-
Neighbourhood components analysis. In: Advances in neural information processing systems vol 17. MIT Press
-
Goldberger J, Roweis S, Hinton G, Salakhutdinov R (2004) Neighbourhood components analysis. In: Advances in neural information processing systems vol 17. MIT Press, pp 513–520
-
(2004)
pp 513–520
-
-
Goldberger, J.1
Roweis, S.2
Hinton, G.3
Salakhutdinov, R.4
-
15
-
-
78149341007
-
Topographic mapping of large dissimilarity datasets
-
Hammer B, Hasenfuss A (2010) Topographic mapping of large dissimilarity datasets. Neural Comput 22(9):2229–2284
-
(2010)
Neural Comput
, vol.22
, Issue.9
, pp. 2229-2284
-
-
Hammer, B.1
Hasenfuss, A.2
-
16
-
-
84894074213
-
Learning vector quantization for (dis-)similarities
-
Hammer B, Hofmann D, Schleif F-M, Zhu X (2013) Learning vector quantization for (dis-)similarities. Neurocomputing 131:43–51. doi:10.1016/j.neucom.2013.05.054
-
(2013)
Neurocomputing
, vol.131
, pp. 43-51
-
-
Hammer, B.1
Hofmann, D.2
Schleif, F.-M.3
Zhu, X.4
-
18
-
-
84901623923
-
Learning interpretable kernelized prototype-based models
-
Hofmann D, Schleif F-M, Hammer B (2013) Learning interpretable kernelized prototype-based models. Neurocomputing 141:84–96. doi:10.1016/j.neucom.2014.03.003
-
(2013)
Neurocomputing
, vol.141
, pp. 84-96
-
-
Hofmann, D.1
Schleif, F.-M.2
Hammer, B.3
-
19
-
-
84937628251
-
-
House TW (2012) Big data research and development initiative. Accessed 1 July 2012
-
House TW (2012) Big data research and development initiative. http://www.whitehouse.gov/blog/2012/03/29/big-data-big-deal. Accessed 1 July 2012
-
-
-
-
20
-
-
32344441116
-
Zupan B (2005) Nomograms for visualizing support vector machines
-
ACM, New York
-
Jakulin A, Možina M, Demšar J, Bratko I, Zupan B (2005) Nomograms for visualizing support vector machines. In: Proceedings of the eleventh ACM SIGKDD international conference on knowledge discovery in data mining, KDD ’05. NY, USA, ACM, New York, pp 108–117
-
Proceedings of the eleventh ACM SIGKDD international conference on knowledge discovery in data mining, KDD ’05. NY, USA
, pp. 108-117
-
-
Jakulin, A.1
Možina, M.2
Demšar, J.3
Bratko, I.4
-
21
-
-
0003505617
-
LVQ\_PAK: the learning vector quantization program package
-
Helsinki University of Technology, Laboratory of Computer and Information Science
-
Kohonen T, Hynninen J, Kangas J, Laaksonen J, Torkkola K (Jan. 1996) LVQ\_PAK: the learning vector quantization program package. Report A30, Helsinki University of Technology, Laboratory of Computer and Information Science
-
(1996)
Report A30
-
-
Kohonen, T.1
Hynninen, J.2
Kangas, J.3
Laaksonen, J.4
Torkkola, K.5
-
22
-
-
33644752875
-
Decision trees for classification: a review and some new results
-
Kothari R, Dong M (2001) Decision trees for classification: a review and some new results. Pattern Recognit 171:169–184
-
(2001)
Pattern Recognit
, vol.171
, pp. 169-184
-
-
Kothari, R.1
Dong, M.2
-
23
-
-
0002229304
-
Pairwise classification and support vector machines
-
Thompson JG, (ed), MIT Press, Cambridge
-
Kreßel UH-G (1999) Pairwise classification and support vector machines. In: Thompson JG (ed) Advances in kernel methods. MIT Press, Cambridge
-
(1999)
Advances in kernel methods
-
-
Kreßel, U.H.-G.1
-
25
-
-
33749258406
-
Kernel clustering-based discriminant analysis
-
Ma B, Qu H, Wong H (2007) Kernel clustering-based discriminant analysis. Pattern Recognit 40(1):324–327
-
(2007)
Pattern Recognit
, vol.40
, Issue.1
, pp. 324-327
-
-
Ma, B.1
Qu, H.2
Wong, H.3
-
26
-
-
0036643059
-
Decision region connectivity analysis: a method for analyzing high-dimensional classifiers
-
Melnik O (2002) Decision region connectivity analysis: a method for analyzing high-dimensional classifiers. Mach Learn 48(1–3):321–351
-
(2002)
Mach Learn
, vol.48
, Issue.1-3
, pp. 321-351
-
-
Melnik, O.1
-
27
-
-
84867656909
-
Safe and interpretable machine learning: a methodological review
-
Moewes C, Nürnberger A, (eds), Springer, Berlin, Heidelberg
-
Otte C (2013) Safe and interpretable machine learning: a methodological review. In: Moewes C, Nürnberger A (eds) Computational intelligence in intelligent data analysis. Studies in computational intelligence. Springer, Berlin, Heidelberg, pp 111–122
-
(2013)
Computational intelligence in intelligent data analysis. Studies in computational intelligence
, pp. 111-122
-
-
Otte, C.1
-
28
-
-
9144260753
-
Improved learning of riemannian metrics for exploratory analysis
-
Peltonen J, Klami A, Kaski S (2004) Improved learning of riemannian metrics for exploratory analysis. Neural Netw 17:1087–1100
-
(2004)
Neural Netw
, vol.17
, pp. 1087-1100
-
-
Peltonen, J.1
Klami, A.2
Kaski, S.3
-
29
-
-
77954608110
-
Visual svm
-
Poulet F (2005) Visual svm. In: Chen C-S, Filipe J, Seruca I, Cordeiro J (eds) ICEIS 2:309–314
-
(2005)
ICEIS
, vol.2
, pp. 309-314
-
-
Poulet, F.1
Chen, C.-S.2
Filipe, J.3
Seruca, I.4
Cordeiro, J.5
-
30
-
-
84937634276
-
-
Roweis S (2012) Machine learning data sets. Accessed 1 July 2012
-
Roweis S (2012) Machine learning data sets. http://www.cs.nyu.edu/~roweis/data.html. Accessed 1 July 2012
-
-
-
-
32
-
-
72249111970
-
Adaptive relevance matrices in learning vector quantization
-
Schneider P, Biehl M, Hammer B (2009) Adaptive relevance matrices in learning vector quantization. Neural Comput 21:3532–3561
-
(2009)
Neural Comput
, vol.21
, pp. 3532-3561
-
-
Schneider, P.1
Biehl, M.2
Hammer, B.3
-
33
-
-
84880051127
-
Using nonlinear dimensionality reduction to visualize classifiers
-
Schulz A, Gisbrecht A, Hammer B (2013) Using nonlinear dimensionality reduction to visualize classifiers. In: Rojas I, Caparrós GJ, Cabestany J (eds) IWANN (1) (Lecture Notes in Computer Science), vol 7902. Springer, pp 59–68
-
(2013)
IWANN (1) (Lecture Notes in Computer Science), vol 7902. Springer
, pp. 59-68
-
-
Schulz, A.1
Gisbrecht, A.2
Hammer, B.3
Rojas, I.4
Caparrós, G.J.5
Cabestany, J.6
-
34
-
-
0038159964
-
Soft learning vector quantization
-
Seo S, Obermayer K (2003) Soft learning vector quantization. Neural Comput 15(7):1589–1604
-
(2003)
Neural Comput
, vol.15
, Issue.7
, pp. 1589-1604
-
-
Seo, S.1
Obermayer, K.2
-
35
-
-
50149098968
-
Visual data mining: theory, techniques and tools for visual analytics (Lecture Notes in Computer Science), vol 4404
-
Simoff SJ, Böhlen MH, Mazeika A editors (2008) Visual data mining: theory, techniques and tools for visual analytics (Lecture Notes in Computer Science), vol 4404. Springer
-
(2008)
Springer
-
-
Simoff, S.J.1
Böhlen, M.H.2
editors, M.A.3
-
36
-
-
0008665337
-
Bandwidth selection in kernel density estimation: a review. In: CORE and Institut de Statistique
-
Turlach BA (1993) Bandwidth selection in kernel density estimation: a review. In: CORE and Institut de Statistique, pp 23–493
-
(1993)
pp 23–493
-
-
Turlach, B.A.1
-
38
-
-
57249084011
-
Visualizing high-dimensional data using t-sne
-
van der Maaten L, Hinton G (2008) Visualizing high-dimensional data using t-sne. J Mach Learn Res 9:2579–2605
-
(2008)
J Mach Learn Res
, vol.9
, pp. 2579-2605
-
-
van der Maaten, L.1
Hinton, G.2
-
39
-
-
38349018685
-
Dimensionality reduction: a comparative review. Technical report, Tilburg University Technical Report
-
van der Maaten L, Postma E, van den Herik H (2009) Dimensionality reduction: a comparative review. Technical report, Tilburg University Technical Report, TiCC-TR 2009–005
-
(2009)
TiCC-TR
, pp. 2005-2009
-
-
van der Maaten, L.1
Postma, E.2
van den Herik, H.3
-
41
-
-
84947754719
-
-
Vellido A, Martin-Guerroro J, Lisboa P (2012) Making machine learning models interpretable. In: ESANN’12
-
Vellido A, Martin-Guerroro J, Lisboa P (2012) Making machine learning models interpretable. In: ESANN’12
-
-
-
-
42
-
-
77949507946
-
Information retrieval perspective to nonlinear dimensionality reduction for data visualization
-
Venna J, Peltonen J, Nybo K, Aidos H, Kaski S (2010) Information retrieval perspective to nonlinear dimensionality reduction for data visualization. J Mach Learn Res 11:451–490
-
(2010)
J Mach Learn Res
, vol.11
, pp. 451-490
-
-
Venna, J.1
Peltonen, J.2
Nybo, K.3
Aidos, H.4
Kaski, S.5
-
43
-
-
33745911895
-
Svmv - a novel algorithm for the visualization of svm classification results
-
Berlin/Heidelberg: Springer
-
Wang X, Wu S, Wang X, Li Q (2006) Svmv - a novel algorithm for the visualization of svm classification results. In: Wang J, Yi Z, Zurada J, Lu B-L, Yin H (eds) Advances in neural networks: ISNN 2006 (Lecture Notes in Computer Science), vol 3971. Berlin/Heidelberg, Springer, pp 968–973
-
(2006)
Advances in neural networks: ISNN 2006 (Lecture Notes in Computer Science)
, vol.3971
, pp. 968-973
-
-
Wang, X.1
Wu, S.2
Wang, X.3
Li, Q.4
Wang, J.5
Yi, Z.6
Zurada, J.7
Lu, B.-L.8
Yin, H.9
-
44
-
-
85077011785
-
-
A. K Peters Ltd, Natick
-
Ward M, Grinstein G, Keim DA (2010) Interactive data visualization: foundations, techniques, and application. A. K Peters Ltd, Natick
-
(2010)
Interactive data visualization: foundations, techniques, and application
-
-
Ward, M.1
Grinstein, G.2
Keim, D.A.3
-
45
-
-
84897521276
-
Scalable optimization of neighbor embedding for visualization. In: Dasgupta S, Mcallester D (eds) Proceedings of the 30th International Conference on Machine Learning (ICML-13), vol 28, pp 127–135
-
Yang Z, Peltonen J, Kaski S (2013) Scalable optimization of neighbor embedding for visualization. In: Dasgupta S, Mcallester D (eds) Proceedings of the 30th International Conference on Machine Learning (ICML-13), vol 28, pp 127–135. JMLR Workshop and Conference Proceedings
-
(2013)
JMLR Workshop and Conference Proceedings
-
-
Yang, Z.1
Peltonen, J.2
Kaski, S.3
|