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Fig. 8 | Cancer Cell International

Fig. 8

From: Deciphering the prognostic features of bladder cancer through gemcitabine resistance and immune-related gene analysis and identifying potential small molecular drug PIK-75

Fig. 8

Hub gene identification by 6 machine learning algorithms. A–F 6 machine learning classifier accuracy (Catboost, Random Forest, GDBT, LGBM, Adaboost, and BSXGB). Red lines represent true data and blue lines represent predicted data. G–L Through six machine learning algorithms (Catboost, Random Forest, GDBT, LGBM, Adaboost, and BSXGB), the contribution value of each gene that makes up the signature to the model is calculated and ranked from largest to smallest. SHAP value represents the absolute average of the effect of each gene on the model

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Cancer Cell International

ISSN: 1475-2867

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