J
Jayanta Basak
Researcher at IBM
Publications - 81
Citations - 1571
Jayanta Basak is an academic researcher from IBM. The author has contributed to research in topics: Artificial neural network & Biology. The author has an hindex of 19, co-authored 67 publications receiving 1429 citations. Previous affiliations of Jayanta Basak include Indian Statistical Institute & University of Chile.
Papers
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Simultaneous feature selection and classification using kernel-penalized support vector machines
TL;DR: An embedded method that simultaneously selects relevant features during classifier construction by penalizing each feature's use in the dual formulation of support vector machines (SVM) called kernel-penalized SVM (KP-SVM).
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Unsupervised feature evaluation: a neuro-fuzzy approach
TL;DR: A way of formulating neuro-fuzzy approaches for both feature selection and extraction under unsupervised learning of a fuzzy feature evaluation index for a set of features is demonstrated.
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Interpretable hierarchical clustering by constructing an unsupervised decision tree
Jayanta Basak,Raghu Krishnapuram +1 more
TL;DR: A theoretical basis for the proposed method for hierarchical clustering based on the decision tree approach is provided and the capability of the unsupervised decision tree for segmenting various data sets is demonstrated.
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Unsupervised feature selection using a neuro-fuzzy approach
TL;DR: A neuro-fuzzy methodology is described which involves connectionist minimization of a fuzzy feature evaluation index with unsupervised training and a set of optimal weighing coefficients in terms of networks parameters representing individual feature importance is obtained.
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Weather Data Mining Using Independent Component Analysis
TL;DR: The independent component analysis technique is applied to mine for patterns in weather data using the North Atlantic Oscillation as a specific example and finds that the strongest independent components match the observed synoptic weather patterns corresponding to the NAO.