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- W4306923114 abstract "In the current era of big data, semi-supervised learning algorithms are widely used. The self-training algorithm is one of the commonly used semi-supervised algorithm frameworks. During the iteration process of the self-training algorithm, the classification performance of the base classifier has a significant influence on the final classifier trained by the model. To study the effect of the base classifier on the performance of the STDPM algorithm, we use KNN, decision tree, and SVM base classifier to conduct experiments on four medical images. The experimental results show that on the four data sets diabetes, heart, hepatitis and Ilpd, the three classifiers KNN (K=1), SVM and decision tree have little effect on the STDPM algorithm. When K=3, the algorithm STDPM performs poorly using the KNN base classifier." @default.
- W4306923114 created "2022-10-21" @default.
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- W4306923114 date "2022-10-20" @default.
- W4306923114 modified "2023-09-27" @default.
- W4306923114 title "Application of classifier based on STDPM algorithm" @default.
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- W4306923114 doi "https://doi.org/10.1117/12.2654556" @default.
- W4306923114 hasPublicationYear "2022" @default.
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