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Results:
1-22
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Results: 22
Authors:
Liu, H
Motoda, H
Citation: H. Liu et H. Motoda, Data reduction via instance selection, KLUW ENGN C, 608, 2001, pp. 3-20
Authors:
Gu, BH
Hu, FF
Liu, H
Citation: Bh. Gu et al., Sampling: Knowing whole from its part, KLUW ENGN C, 608, 2001, pp. 21-38
Authors:
Reinartz, T
Citation: T. Reinartz, A unifying view on instance selection, KLUW ENGN C, 608, 2001, pp. 39-56
Authors:
Smyth, B
McKenna, E
Citation: B. Smyth et E. Mckenna, Competence guided instance selection for case-based reasoning, KLUW ENGN C, 608, 2001, pp. 59-76
Authors:
Brighton, H
Mellish, C
Citation: H. Brighton et C. Mellish, Identifying competence-critical instances for instance-based learners, KLUW ENGN C, 608, 2001, pp. 77-94
Authors:
Ishibuchi, H
Nakashima, T
Nii, M
Citation: H. Ishibuchi et al., Genetic-algorithm-based instance and feature selection, KLUW ENGN C, 608, 2001, pp. 95-112
Authors:
Perng, CS
Zhang, SR
Parker, DS
Citation: Cs. Perng et al., The landmark model: An instance selection method for time series data, KLUW ENGN C, 608, 2001, pp. 113-130
Authors:
Domingo, C
Gavalda, R
Watanabe, O
Citation: C. Domingo et al., Adaptive sampling methods for scaling up knowledge discovery algorithm., KLUW ENGN C, 608, 2001, pp. 133-150
Authors:
Provost, F
Jensen, D
Oates, T
Citation: F. Provost et al., Progressive sampling, KLUW ENGN C, 608, 2001, pp. 151-170
Authors:
Chauchat, JH
Rakotomalala, R
Citation: Jh. Chauchat et R. Rakotomalala, Sampling strategy for building decision trees from very large databases comprising many continuous attributes, KLUW ENGN C, 608, 2001, pp. 171-188
Authors:
Yoon, H
AlSabti, K
Ranka, S
Citation: H. Yoon et al., Incremental classification using tree-based sampling for large data, KLUW ENGN C, 608, 2001, pp. 189-206
Authors:
Madigan, D
Raghavan, N
DuMouchel, M
Nason, M
Posse, C
Ridgeway, G
Citation: D. Madigan et al., Instance construction via likelihood-based data squashing, KLUW ENGN C, 608, 2001, pp. 209-226
Authors:
Lam, W
Keung, CK
Ling, CX
Citation: W. Lam et al., Learning via prototype generation and filtering, KLUW ENGN C, 608, 2001, pp. 227-244
Authors:
Wang, H
Citation: H. Wang, Instance selection based on hypertuples, KLUW ENGN C, 608, 2001, pp. 245-262
Authors:
Wright, P
Hodges, J
Citation: P. Wright et J. Hodges, KbIS: Using domain knowledge to guide instance selection, KLUW ENGN C, 608, 2001, pp. 263-279
Authors:
Skalak, DB
Citation: Db. Skalak, Instance sampling for boosted and standalone nearest neighbor classifiers, KLUW ENGN C, 608, 2001, pp. 283-300
Authors:
Nock, R
Sebban, M
Citation: R. Nock et M. Sebban, Prototype Selection using boosted nearest-neighbors, KLUW ENGN C, 608, 2001, pp. 301-318
Authors:
Davies, W
Edwards, P
Citation: W. Davies et P. Edwards, DAGGER: Instance selection for combining multiple models learnt from disjoint subsets, KLUW ENGN C, 608, 2001, pp. 319-336
Authors:
Reeves, CR
Bush, DR
Citation: Cr. Reeves et Dr. Bush, Using genetic algorithms for training data selection in RBF networks, KLUW ENGN C, 608, 2001, pp. 339-356
Authors:
Sung, KK
Niyogi, P
Citation: Kk. Sung et P. Niyogi, An active learning formulation for instance selection with applications toobject detection, KLUW ENGN C, 608, 2001, pp. 357-374
Authors:
Gamberger, D
Lavrac, N
Citation: D. Gamberger et N. Lavrac, Filtering noisy instances and outliers, KLUW ENGN C, 608, 2001, pp. 375-394
Authors:
Sugaya, S
Suzuki, E
Tsumoto, S
Citation: S. Sugaya et al., Instance selection based on support vector machine for knowledge discoveryin medical database, KLUW ENGN C, 608, 2001, pp. 395-412
Risultati:
1-22
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