N. Jankowski, "Approximation and classification in medicine with IncNet neural networks." In: Machine Learning and Applications. Workshop on Machine Learning in Medical Applications, Chania, Greece, pp. 5358, 1999. Home/Search Document Details and Download
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Probabilistic Intervals of Confidence - Jankowski Self-citation (Jankowski) (Correct)
....M) is found for class k. p(C i x; M) describe probability for model M that given input vector x belong to class i. Let the function C(x) argm ax i p(C i x; M) 1) i.e. C(x) is equal to the index k of the most probable class for the input vector x. The Incremental Network (IncNet) [4, 2, 3, 5] was used to compute probability p(C k x; M) In general such probability may be estimated by any trustworthy model. The IncNet network was used because of its good performance network structure is controlled by growing and pruning criterion to keep complexity of network similar to the ....
....classified as normal or belong to a disease such as neurosis, psychopathy, schizophrenia, delusions, psychosis, etc. Data sets consists of 1027 and 1167 examples respectively for 27 and 28 classes sets. To illustrate some results conditional probabilities will be estimated using IncNet classifier [4, 2, 3, 5]. Figures 1 and 2 show probabilistic intervals of confidence for two quite 0 20 40 60 80 100 120 0 0.2 0.4 0.6 0.8 1 psychopathy manic state schizophrenia Feature value Probability 1. Assessment of degree of sincerity 0 20 40 60 80 100 120 0 0.2 0.4 0.6 0.8 1 psychopathy Feature value ....
N. Jankowski. Approximation and classification in medicine with IncNet neural networks. In Machine Learning and Applications. Workshop on Machine Learning in Medical Applications, pages 53--58, Chania, Greece, July 1999. (PDF).
Simultaneous Differential Diagnoses Basing on MMPI Inventory .. - Jankowski, Gomula Self-citation (Jankowski) (Correct)
....of patient population over nosological type women data set 1234567891011121314151617181920 269 218 42 78 459 21 37 32 35 81 23 52 203 43 41 26 14 13 12 12 Differential diagnoses using classification models. We used two different classification systems: Incremental Network (IncNet) [6, 5, 7] and decision tree C 4.5 for rule extraction [10] Structure of incremental neural network is controlled by growing and pruning to match the complexity of training data. Extended Kalman Filter algorithm and its fast version is used as learning algorithm. Bi radial transfer functions, more flexible ....
....network is controlled by growing and pruning to match the complexity of training data. Extended Kalman Filter algorithm and its fast version is used as learning algorithm. Bi radial transfer functions, more flexible than other functions commonly used in artificial neural networks, are used. See [6, 5, 7] for more datails. Table 1 compares generalization performance of IncNet and C 4.5 for to data sets: 27 and 28 class in cross validation tests. Results clearly show the higher performance of IncNet model. Probabilistic confidence intervals answer the question: How the probabilities of the ....
N. Jankowski. Approximation and classification in medicine with IncNet neural networks. In Machine Learning and Applications. Workshop on Machine Learning in Medical Applications, pages 53--58, Chania, Greece, July 1999.(PDF).
Probabilistic Intervals of Confidence - Jankowski (2000) Self-citation (Jankowski) (Correct)
....M) is found for class k. p(C i x; M) describe probability for model M that given input vector x belong to class i. Let the function C(x) arg max i p(C i x; M) 1) i.e. C(x) is equal to the index k of the most probable class for the input vector x. The Incremental Network (IncNet) [4, 2, 3, 5] was used to compute probability p(C k x; M) In general such probability may be estimated by any trustworthy model. The IncNet network was used because of its good performance network structure is controlled by growing and pruning criterion to keep complexity of network similar to the ....
....as normal or belong to a disease such as neurosis, psychopathy, schizophrenia, delusions, psychosis, etc. Data sets consists of 1027 and 1167 examples respectively for 27 and 28 classes sets. To illustrate some results conditional probabilities will be estimated using IncNet classifier [4, 2, 3, 5]. Figures 1 and 2 show probabilistic intervals of confidence for two quite 0 20 40 60 80 100 120 0 0.2 0.4 0.6 0.8 1 psychopathy manic state schizophrenia Feature value 1. Assessment of degree of sincerity 0 20 40 60 80 100 120 0 0.2 0.4 0.6 0.8 1 psychopathy Feature value Probability 2. ....
N. Jankowski. Approximation and classification in medicine with IncNet neural networks. In Machine Learning and Applications. Workshop on Machine Learning in Medical Applications, pages 53--58, Chania, Greece, July 1999. (PDF).
Uncertainty of Data, Fuzzy Membership Functions, and Multi-Layer.. - Duch (2004) (Correct)
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N. Jankowski, "Approximation and classification in medicine with IncNet neural networks." In: Machine Learning and Applications. Workshop on Machine Learning in Medical Applications, Chania, Greece, pp. 5358, 1999.
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