Figure 1. The workflow of the performance-weighted-voting model.

The performance-weighted-voting model integrates five classifiers including logistic regression, SVM, random forest, XGBoost and neural networks. We first used cross-validation to get the predicted results for the five classifiers. The weights of the five weak classifiers can be obtained based on their predictive performance by solving linear regression functions. The final predicted probability of the performance-weighted-voting model for a cancer type can be determined by the summation of each classifier’s weight multiplied by its predicted probability.