Indexed keywords
ALGORITHMS;
DIAGNOSIS;
DISEASES;
DIFFERENTIAL DIAGNOSIS;
VOTING FEATURE INTERVALS;
COMPUTER AIDED DIAGNOSIS;
ALGORITHM;
ARTICLE;
ARTIFICIAL INTELLIGENCE;
DIFFERENTIAL DIAGNOSIS;
DISEASE CLASSIFICATION;
ERYTHEMATOSQUAMOUS SKIN DISEASE;
LEARNING;
PREDICTION;
PRIORITY JOURNAL;
SYSTEM ANALYSIS;
ALGORITHMS;
DECISION SUPPORT SYSTEMS, CLINICAL;
DIAGNOSIS, DIFFERENTIAL;
HUMANS;
SKIN DISEASES, PAPULOSQUAMOUS;
2
0010455575
K nearest neighbor classification on feature projections
Akkuş A, Güvenir HA. K Nearest Neighbor classification on Feature Projections. In: Proc. ICML' 96, 1995:12-19.
(1995)
Proc. ICML' 96
, pp. 12-19
Akkuş, A.1
Güvenir, H.A.2
3
0028496468
Learning boolean concepts in the presence of many irrelevant features
Almnallim H, Dietterich TG Learning boolean concepts in the presence of many irrelevant features. Artif Intell. 69:1994;279-305.
(1994)
Artif Intell
, vol.69
, pp. 279-305
Almnallim, H.1
Dietterich, T.G.2
4
34250080806
A Weighted Nearest Neighbor Algorithm for Learning with Symbolic Features
Cost S, Salzberg S A Weighted Nearest Neighbor Algorithm for Learning with Symbolic Features. Mach Learn. 10:1993;57-78.
(1993)
Mach Learn
, vol.10
, pp. 57-78
Cost, S.1
Salzberg, S.2
5
0002949602
Genetic algorithms to learn feature weights for the nearest neighbor algorithm
Demiröz G, Güvenir HA. Genetic Algorithms to Learn Feature Weights for the Nearest Neighbor Algorithm. In: Proc BENELEARN-96, 1996:117-126.
(1996)
Proc BENELEARN-96
, pp. 117-126
Demiröz, G.1
Güvenir, H.A.2
7
0026205055
DIAGAID: A connectionist approach to determine the diagnostic value of clinical data
Forsström J, Eklund P, Virtanen H, Waxlax J, Lähbdevirta J DIAGAID: a connectionist approach to determine the diagnostic value of clinical data. Artif Intell Med. 3:1991;193-201.
(1991)
Artif Intell Med
, vol.3
, pp. 193-201
Forsström, J.1
Eklund, P.2
Virtanen, H.3
Waxlax, J.4
Lähbdevirta, J.5
8
0030130153
Classification by Feature Partitioning
Güvenir HA, Şirin I. Classification by Feature Partitioning. Mach Learn. 23:1996;47-67.
(1996)
Mach Learn
, vol.23
, pp. 47-67
Güvenir, H.A.1
Şirin, I.2
9
0027580356
Very simple classification rules perform well on most commonly used datasets
Holte RC Very simple classification rules perform well on most commonly used datasets. Mach Learn. 11:1993;63-91.
(1993)
Mach Learn
, vol.11
, pp. 63-91
Holte, R.C.1
10
0027682531
Inductive and Bayesian Learning in Medical Diagnosis
Kononenko I Inductive and Bayesian Learning in Medical Diagnosis. Appl Artif Intell. 7:1993;317-337.
(1993)
Appl Artif Intell
, vol.7
, pp. 317-337
Kononenko, I.1
11
0025803268
Information-Based Evaluation Criterion for classifier's Performance
Kononenko I, Bratko I Information-Based Evaluation Criterion for classifier's Performance. Mach Learn. 6:1991;67-80.
(1991)
Mach Learn
, vol.6
, pp. 67-80
Kononenko, I.1
Bratko, I.2
13
0342711245
Case-based learning of plans and goal states in medical diagnosis
Lopez B, Plaza E Case-based learning of plans and goal states in medical diagnosis. Artif Intell Med. 6:1997;29-60.
(1997)
Artif Intell Med
, vol.6
, pp. 29-60
Lopez, B.1
Plaza, E.2
15
85152587599
Learning categorical decision criteria in biomedical domains
University of Michigan, Ann Arbor
Spackman AK. Learning Categorical Decision Criteria in Biomedical Domains. In: Proc 5th International Conference on Machine Learning. University of Michigan, Ann Arbor, 1988:36-46.
(1988)
Proc 5th International Conference on Machine Learning.
, pp. 36-46
Spackman, A.K.1