We adopt a four step evaluation methodology to ensure an unbiased evaluation of differ- ent machine learning schemes: (1) preprocessing the dataset using attribute selection to remove redundant and useless features, (2) providing the preprocessed features' set to six well-known classification algorithms, (3) bagging ...
This paper provides a comprehensive evaluation of a set of diverse machine learning schemes on a number of biomedical datasets. ... Using this methodology, we ...
The important outcome of this extensive study is a set of promising guidelines which will help researchers in choosing the best classification scheme for a ...
Guidelines to Select Machine Learning Scheme for Classification ...
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Abstract. Biomedical datasets pose a unique challenge to machine learning and data mining algorithms for classification because of their high dimensionality ...
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Guidelines to Select Machine Learning Scheme for Classification of Biomedical Datasets. https://doi.org/10.1007/978-3-642-01184-9_12 · Full text.
Dec 16, 2021 · We describe several supervised and unsupervised ML techniques, and illustrate a series of prototypical examples using state-of-the-art computational approaches.
Machine Learning Scheme - an overview | ScienceDirect Topics
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Machine learning schemes include information theory, neural networks, support vector machines, genetic algorithms, and many more (Sommer and Paxson, 2010).
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Oct 18, 2022 · In this post, we'll briefly discuss challenges you face when working with medical data and make an overview of publicly available healthcare datasets.
Missing: Guidelines Scheme
May 13, 2020 · Training and testing process for the classification of biomedical datasets in machine learning is very important.
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