Abstract
Until now we have discussed the general concepts and models of Machine Learning algorithm, here we will move deeper into the understanding of these methods and models in biological data. Feature extraction and Dimensionality reduction are important methods used in Biology and Healthcare. The relevance of these techniques is more due to the use of sensors and multi-modal data sources. There are number of feature extraction techniques grouped under the Multivariate Analysis (MVA). In this chapter we will discuss Parameter Estimation, Estimation of Missing Values, Multivariate Normal Distribution, Multivariate Classification, and Tuning Complexity in the context of analysis of biological data.
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Ghosh, S., Dasgupta, R. (2022). Multivariate Methods in Machine Learning in the Context of Biological Data. In: Machine Learning in Biological Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-16-8881-2_6
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DOI: https://doi.org/10.1007/978-981-16-8881-2_6
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