-
3
-
-
84936937316
-
Analysis and improvements of the adaptive discretization intervals knowledge representation
-
Bacardit J,Garrell JM (2004) Analysis and improvements of the adaptive discretization intervals knowledge representation. In: GECCO, vol 2, pp 726-738
-
(2004)
GECCO
, vol.2
, pp. 726-738
-
-
Bacardit, J.1
Garrell, J.M.2
-
4
-
-
84873117260
-
Coala: A novel approach for the extraction of an alternate clustering of high quality and high dissimilarity
-
Bae E, Bailey J (2006) Coala: A novel approach for the extraction of an alternate clustering of high quality and high dissimilarity. In: International conference on data mining, pp 53-62
-
(2006)
International Conference on Data Mining
, pp. 53-62
-
-
Bae, E.1
Bailey, J.2
-
9
-
-
84880095768
-
Clustering with constraints: Feasibility issues and the k-means algorithm
-
Davidson I (2005a) Clustering with constraints: Feasibility issues and the k-means algorithm. In: SIAM international conference on data mining
-
(2005)
SIAM International Conference on Data Mining
-
-
Davidson, I.1
-
10
-
-
33646435064
-
Agglomerative hierarchical clusteringwith constraints: Theoretical and empirical results
-
Davidson I (2005b) Agglomerative hierarchical clusteringwith constraints: Theoretical and empirical results. In: Pacific Asia conference on knowledge discovery, pp 59-70
-
(2005)
Pacific Asia Conference on Knowledge Discovery
, pp. 59-70
-
-
Davidson, I.1
-
12
-
-
0015644825
-
A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters
-
Dunn J (1974) A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters. J Cybern 3:32-57
-
(1974)
J Cybern
, vol.3
, pp. 32-57
-
-
Dunn, J.1
-
13
-
-
0041078536
-
A direct method for multidimensional ratio scaling
-
Ekman G (1963) A direct method for multidimensional ratio scaling. Psychometrika 28(1):33-41
-
(1963)
Psychometrika
, vol.28
, Issue.1
, pp. 33-41
-
-
Ekman, G.1
-
14
-
-
0012834533
-
Why so many clustering algorithms: A position paper
-
Estivill-Castro V (2002) Why so many clustering algorithms: A position paper. SIGKDD Explor Newsl 4(1):65-75
-
(2002)
SIGKDD Explor Newsl
, vol.4
, Issue.1
, pp. 65-75
-
-
Estivill-Castro, V.1
-
15
-
-
0003024008
-
On the handling of continuous-valued attributes in decision tree generation
-
Fayyad UM, Irani KB (1992) On the handling of continuous-valued attributes in decision tree generation. Mach Learn 8:87-102
-
(1992)
Mach Learn
, vol.8
, pp. 87-102
-
-
Fayyad, U.M.1
Irani, K.B.2
-
17
-
-
21244468777
-
Combining multiple clusterings using evidence accumulation
-
Fred ALN, Jain AK (2005) Combining multiple clusterings using evidence accumulation. IEEE Trans Pattern Anal Mach Intell 27(6):835-850
-
(2005)
IEEE Trans Pattern Anal Mach Intell
, vol.27
, Issue.6
, pp. 835-850
-
-
Fred, A.L.N.1
Jain, A.K.2
-
21
-
-
33747044600
-
Metric and dissimilarity properties of dissimilarity coefficients
-
Gower JC, Legendre P (1986) Metric and dissimilarity properties of dissimilarity coefficients. J Classif 3:5-48
-
(1986)
J Classif
, vol.3
, pp. 5-48
-
-
Gower, J.C.1
Legendre, P.2
-
23
-
-
0024904643
-
Similarity measures in scientometric research: The Jaccard index versus Salton's cosine formula
-
Hamers L, Hemeryck Y, Herweyers G, Janssen M, Keters H, Rousseau R, Vanhoutte A (1989) Similarity measures in scientometric research: The Jaccard index versus Salton's cosine formula. Inf Process Manag 25(3):315-318
-
(1989)
Inf Process Manag
, vol.25
, Issue.3
, pp. 315-318
-
-
Hamers, L.1
Hemeryck, Y.2
Herweyers, G.3
Janssen, M.4
Keters, H.5
Rousseau, R.6
Vanhoutte, A.7
-
24
-
-
0000008146
-
Comparing partitions
-
Hubert L, Arabie P (1985) Comparing partitions. J Classif 2(1):193-218
-
(1985)
J Classif
, vol.2
, Issue.1
, pp. 193-218
-
-
Hubert, L.1
Arabie, P.2
-
27
-
-
0002719797
-
The Hungarian method for the assignment problem
-
Kuhn HW (1955) The Hungarian method for the assignment problem. Naval Res Logist Q 2:83-97
-
(1955)
Naval Res Logist Q
, vol.2
, pp. 83-97
-
-
Kuhn, H.W.1
-
29
-
-
1542299386
-
-
Technical Report, Department of Statistics, University of Washington
-
Meila M (2002) Comparing clusterings. Technical Report, Department of Statistics, University of Washington
-
(2002)
Comparing Clusterings
-
-
Meila, M.1
-
30
-
-
77958023407
-
-
Comparing clusterings-technical report
-
Meila M (2003) Comparing clusterings-technical report. http://citeseer.ist.psu.edu/meila02comparing. html
-
(2003)
-
-
Meila, M.1
-
31
-
-
31844440880
-
Comparing clusterings-an axiomatic view
-
MeilaM(2005) Comparing clusterings-an axiomatic view. In: International conference on machine learning Meil?a M (2005) Comparing clusterings: An axiomatic view. In: Proceedings of the 22nd international conference on Machine learning, pp 577-584
-
(2005)
International Conference on Machine Learning
, pp. 577-584
-
-
Meila, M.1
-
32
-
-
77958026381
-
-
Mixed Integer Linear Programming (MILP) Solver
-
Mixed Integer Linear Programming (MILP) Solver (2007). http://lpsolve.sourceforge.net
-
(2007)
-
-
-
34
-
-
84950632109
-
Objective criteria for the evaluation of clustering methods
-
Rand W (1971a) Objective criteria for the evaluation of clustering methods. J Am Stat Assoc 66: 846-850
-
(1971)
J Am Stat Assoc
, vol.66
, pp. 846-850
-
-
Rand, W.1
-
35
-
-
84950632109
-
Objective criteria for the evaluation of clusteringmethods
-
RandWM (1971b) Objective criteria for the evaluation of clusteringmethods. JAmStat Assoc 66:622-626
-
(1971)
JAmStat Assoc
, vol.66
, pp. 622-626
-
-
Rand, W.M.1
-
37
-
-
77958036111
-
-
Repository U (2008) http://archive.ics.uci.edu/ml
-
(2008)
-
-
Repository, U.1
-
38
-
-
84948970450
-
Class-driven statistical discretization of continuous attributes (extended abstract)
-
Springer, London, UK
-
Richeldi M, Rossotto M (1995) Class-driven statistical discretization of continuous attributes (extended abstract). In: Proceedings of the 8th European conference on machine learning. Springer, London, UK, pp 335-338
-
(1995)
Proceedings of the 8th European Conference on Machine Learning
, pp. 335-338
-
-
Richeldi, M.1
Rossotto, M.2
-
39
-
-
0041965980
-
Cluster ensembles-A knowledge reuse framework for combining multiple partitions
-
Strehl A, Ghosh J (2003) Cluster ensembles-a knowledge reuse framework for combining multiple partitions. J Mach Learn 3:583-617
-
(2003)
J Mach Learn
, vol.3
, pp. 583-617
-
-
Strehl, A.1
Ghosh, J.2
-
44
-
-
30144442247
-
Clustering ensembles: Models of consensus and weak partitions
-
Topchy A, Jain AK (2005) Clustering ensembles: Models of consensus and weak partitions. IEEE Trans Pattern Anal Mach Intell 27(12):1866-1881
-
(2005)
IEEE Trans Pattern Anal Mach Intell
, vol.27
, Issue.12
, pp. 1866-1881
-
-
Topchy, A.1
Jain, A.K.2
-
46
-
-
19544373948
-
Analysis of consensus partition in cluster ensemble
-
Topchy A, Martin H, Law C, Jain A, Fred A (2004b) Analysis of consensus partition in cluster ensemble. In: International conference on data mining, pp 225-232
-
(2004)
International Conference on Data Mining
, pp. 225-232
-
-
Topchy, A.1
Martin, H.2
Law, C.3
Jain, A.4
Fred, A.5
-
48
-
-
1842641692
-
Comment
-
Wallace DL (1983) Comment. J Am Stat Assoc 78(383):569-576
-
(1983)
J Am Stat Assoc
, vol.78
, Issue.383
, pp. 569-576
-
-
Wallace, D.L.1
-
49
-
-
58149195307
-
Discretization for naive-bayes learning: Managing discretization bias and variance
-
Yang Y,Webb GI (2009) Discretization for naive-bayes learning: Managing discretization bias and variance. Mach Learn 74(1):39-74
-
(2009)
Mach Learn
, vol.74
, Issue.1
, pp. 39-74
-
-
Yang, Y.1
Webb, G.I.2
|