Table 12 Compare the accuracy of all algorithms on malaria and typhoid datasets using correlated features
From: Machine learning based efficient prediction of positive cases of waterborne diseases
Model | Accuracy | |
|---|---|---|
Comparison of all algorithm results malaria dataset | ||
Decision tree algorithm Random forest algorithm Support vector machine algorithm Logistics Regression algorithm KNN algorithm | 0.6421 0.7453 0.5779 0.5779 0.5789 | |
Comparison of all algorithms results typhoid dataset | ||
Decision tree algorithm Random forest algorithm Support vector machine algorithm Logistics Regression algorithm KNN algorithm | 0.5982 0.601 0.5957 0.5956 0.597 | |