Abstract: In this research paper we have compared different models of classification using csv dataset and we tried to find out which one of them best fits for the dataset to predict the drug type and then predict the drug type based on the input features of the patient. We have performed this problem in the python programming language on Google Colab. We have used a lot of libraries and packages for the implementation of classifiers and also for plotting graph, making table, finding errors, accuracies confusion matrices etc. The dataset has a lot of classes in which the outcomes are classified and a lot of parameters which are used for the prediction of the outcomes. We have made tables for the comparison also plotted the graphs for the prediction and then we have compared the models for which among them has better efficiency for that particular dataset.

Keywords: Artificial Intelligence (AI), Machine Learning (ML), Drug Type Prediction, Support Vector Machine (SVM); Naïve Bayes, k-nearest neighbours, Random Forest, Logistic Regression.

| DOI: 10.17148/IARJSET.2025.12612