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. 2021 Oct 26;7(11):225. doi: 10.3390/jimaging7110225

Table 2.

Comparison of different classification methods on WBCD after feature scaling, and hyper-parameter tuning of features using PCA and correlation analysis.

Classification Algorithms Accuracy Precision Recall F-Measures F2-Measures
Simple Logistic Regression Learning 97.49% 97.89% 95.21% 96.53% 95.73%
K-Nearest Neighbor Classification 97.49% 98.48% 89.70% 93.88% 91.32%
Support Vector Machine 96.23% 91.88% 93.94% 92.89% 93.52%
Random Decision Forest 94.22% 93.86% 82.88% 88.02% 84.86%
Stochastic Gradient Descent Learning 92.11% 84.38% 89.20% 86.72% 88.19%
Decision Tree 90.45% 87.14% 87.00% 87.06% 87.02%
Naïve Bayes Classification 91.60% 91.90% 91.80% 91.84% 91.81%