Here we are predict the water quality level in water and it is a supervised machine learning algorithm use in this dataset.
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Business Case:- Here we are predict the water quality level in water and decied the based on different column in this dataset like aluminium, ammonia, arsenic , barium, cadmium, chloramine, chromium,copper, flouride, bacteria, viruses ,lead, nitrates, nitrites, mercury, perchlorate, radium, selenium ,silver ,uranium ,is_safe.
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Final Usecase:- Here we can are use the total 10 algorithm in this dataset like Logistic Regression, SVM Algorithm, DecisionTreeClassifier, KNN ALgorithm, Bagging Algorithm, RandomForestClassifier, GradiantBoostingClassifier, XGBClassifierAddaBoostingClassifier, ANN_MLPClassifier. Here we can see the Highest model accuracy_score provide XGBClassifier Algorithm is 96.35 and f1_score is 96.35. Here we can see the Highest model accuracy_score provide DecisionTree Algorithm is 94.40 and f1_score is 94.57.