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©The Author(s) 2022.
World J Gastroenterol. Sep 28, 2022; 28(36): 5338-5350
Published online Sep 28, 2022. doi: 10.3748/wjg.v28.i36.5338
Published online Sep 28, 2022. doi: 10.3748/wjg.v28.i36.5338
Figure 2 Variable screening and weight allocation.
A: Correlation matrix analysis of candidate features; B: Weight distribution of candidate variables for each mL based model. RFC: Random forest classifier; SVM: Support vector machine; DT: Decision tree; ANN: Artificial neural network; XGboost: Extreme gradient boosting.
- Citation: Wei X, Yan XJ, Guo YY, Zhang J, Wang GR, Fayyaz A, Yu J. Machine learning-based gray-level co-occurrence matrix signature for predicting lymph node metastasis in undifferentiated-type early gastric cancer. World J Gastroenterol 2022; 28(36): 5338-5350
- URL: https://www.wjgnet.com/1007-9327/full/v28/i36/5338.htm
- DOI: https://dx.doi.org/10.3748/wjg.v28.i36.5338