Table 1.
Dataset parameter/attributes.
Fig 1.
Proposed architecture.
Fig 2.
Target variable distribution.
Fig 3.
Age distribution among patients.
Fig 4.
Gender classification.
Fig 5.
Correlation matrix.
Table 2.
Performance metrics of random forest classifier for liver disease prediction.
Table 3.
Performance metrics of Ada Boost classifier for liver disease prediction.
Table 4.
Performance metrics of gradient boosting classifier for liver disease prediction.
Table 5.
Classifier performance.
Fig 6.
Classifier accuracy comparison.