A Machine Learning-Based Water Potability Prediction Model by Using Synthetic Minority Oversampling Technique and Explainable AI

Table 3

Comparative analysis of different classifiers.

Classifiers	Accuracy
Random Forest	0.80
Gradient Boost	0.76
Decision Tree	0.73
Support Vector	0.69
AdaBoost	0.68
Support Vector	0.67
KNeighbors	0.65
BernouliNB	0.61
GaussianNB	0.57
Passive aggressive	0.54
Nearest centroid	0.52
Logistic regression	0.52
Ridge	0.52
Stochastic gradient descent	0.51
Perceptron	0.51