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Good methods for coping with missing data in decision trees
Good methods for coping with missing data in decision treesAuthor links open overlay panelB.E.T.H.TwalaaM.C.JonesbD.J.Handchttps://doi.org/10.1016/j.patrec.2008.01.010Get rights and contentAbstractWe ... [Read More]
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High-performance exclusion of schizophrenia using a novel machine learning method on EEG data | IEEE Conference Publication | IEEE Xplore
Abstract:Using the Random Forest method, we developed a fast-high-performance classification model, which can exclude a potential schizophrenic disorder in a diagnosis of potentially exposed peo... [Read More]
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Machine Learning for the Biochemical Genetics Laboratory | Clinical Chemistry | Oxford Academic
Machine learning has emerged as an indispensable part of modern data analysis, particularly for classifying samples based on complex sets of variables. In the r [Read More]
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Support vector machine-based classification of schizophrenia patients and healthy controls using structural magnetic resonance imaging from two independent sites
Structural brain alterations have been repeatedly reported in schizophrenia; however, the pathophysiology of its alterations remains unclear. Multivariate pattern recognition analysis such as support ... [Read More]
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Frontiers | Predicting SSRI-Resistance: Clinical Features and tagSNPs Prediction Models Based on Support Vector Machine | Psychiatry
Background: A large proportion of major depressive patients will experience recurring episodes. Many patients still do not response to available antidepressants. In order to meaningfully predict who w... [Read More]
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