Prediction of Brand Loyalty on Supervised Machine Learning Algorithms

Supervised Machine Learning (SML) is the quest for algorithms that explanation from remotely provided occurrences to deliver general speculations, which then make predictions about future instances.The present exploration investigates the loyalty prediction issue of a brand through supervised learning algorithms of characterizations: logistic regression, decision tree, support vector machine, bayes algorithm and K-nearest neighbors (KNN) algorithm. 265 clients' FMCG loyalty test information were taken and factors of the informational collection incorporate; loyalty status, orientation, family size, age, recurrence of procurement, and FMCG buy. Information have been investigated with the assistance of Python packages like Pandas(Data analysis), Numpy (Mathematical estimation), Matplotlib (Visualization), and Sklearn (Displaying)