Semi-Supervised Self-Training Feature Weighted Clustering Decision Tree and Random Forest
IEEE Access, pp. 128337-128348, 2020.
A self-training algorithm is an iterative method for semi-supervised learning, which wraps around a base learner. It uses its own predictions to assign labels to unlabeled data. For a self-training algorithm, the classification ability of the base learner and the estimation of prediction confidence are very important. The classical decisi...More
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