**3.4 Algorithms selection from common algorithms**

Several algorithms exist for anomaly detection systems. For the execution of detection falls, we shall utilize eight different machine learning algorithms [25]. These algorithms would be compared, and the best should be used in the application of the smart house. Eight algorithms are selected for this experiment as follows. Logistic

regression, Linear discriminate analysis (LAD), k-nearest neighbors (k-NN), decision tree classifier, Gaussian naive Bayes, Support Vector Machine (SVM), Random Forest, and xgboost algorithms. The best performing among these algorithms is to be utilized. The algorithm's performance would have to be weighed by the following parameters.
