Comparison of the classification accuracy of different class imbalance models with classifiers on LIHC dataset.

Comparison of the classification accuracy of different class imbalance models with classifiers on LIHC dataset.</p

Number of original features (before PCA), and number of features after dimensionality reduction using PCA.

Number of original features (before PCA), and number of features after dimensionality reduction using PCA.</p

Comparison of recall of different class imbalance models with classifiers on LIHC dataset.

Comparison of recall of different class imbalance models with classifiers on LIHC dataset.</p

Summary of the classification performance on the datasets of different cancer types.

Summary of the classification performance on the datasets of different cancer types.</p

Comparison of F1 score of different class imbalance models with classifiers on LIHC dataset.

Comparison of F1 score of different class imbalance models with classifiers on LIHC dataset.</p

Comparison of the performance metrics of different classifiers for LIHC.

Comparison of the performance metrics of different classifiers for LIHC.</p

Comparison of the performance metrics of different classifiers for COAD.

Comparison of the performance metrics of different classifiers for COAD.</p

Comparison of precision of different class imbalance models with classifiers on LIHC dataset.

Comparison of precision of different class imbalance models with classifiers on LIHC dataset.</p

Comparison of the performance metrics of different classifiers for BRCA.

Comparison of the performance metrics of different classifiers for BRCA.</p

Summary of SMOTE’s effect on different cancer types.

Summary of SMOTE’s effect on different cancer types.</p