Research Article
RNA-Seq-Based Breast Cancer Subtypes Classification Using Machine Learning Approaches
Table 3
RNA-Seq-based BRCA subtypes classification using 5-fold cross-validation with 100 repeats. The first column denotes the five kinds of subtypes, and we built a binary classifier for each subtype by splitting the data into control and experiment groups. The sample size of two groups was imbalanced, so the “SMOTE” sampling method in the second column was utilized to lessen the interference of imbalanced data. The “LumA” subtype was an exception because it had sufficient samples. The third column denotes the five kinds of metrics used in this experiment, and the remaining columns are the three kinds of machine learning approaches adopted in this research, where the “svmRadial” represents the svm with radial basis kernel.
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