Comprehensive Analysis of Lung Cancer Classification Using Gaussian Process Classifier: Unveiling Exceptional Performance and Clinical Implications

In this analysis, the performance of the Gaussian Process Classifier (GPC) was evaluated for classifying instances of lung cancer using various metrics. The GPC model achieved impressive results, with accuracy ranging from approximately 83.87% to 96.67%. Precision values ranged from 75.86% to 96.79%, recall values ranged from 83.87% to 96.67%, and F1-score values ranged from 81.09% to 96.36%. These metrics highlight the GPC model’s exceptional performance in accurately classifying lung cancer cases. The findings from this analysis have significant implications for improving lung cancer diagnosis, treatment planning, and ultimately enhancing patient outcomes.