A survey on common biostatistics tools in neuroscience: Machine learning and Bayesian modeling
Ziyi Xue
Abstract:Machine learning was characterized by building models and finding correlations between data features, while logistic regression, decision trees, support vector machines (SVM), random forest (RF) and neural networks were recognized as common ML approaches. Bayesian modeling model uncertainty, which can estimate the features from the dataset directly instead of from sampling distribution. Their roles were extremely useful for the detection and progression for diseases in neuroscience. This review summarize diffe… Show more
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