This dataset contains information about a set of patients who suffered from the same illness and were treated with one of five medications: Drug A, Drug B, Drug C, Drug X, and Drug Y. The goal is to build a model to predict which drug might be appropriate for future patients based on their characteristics.
Age: The age of the patient. Sex: The sex of the patient (Male or Female). Blood Pressure (BP): The blood pressure level of the patient, categorized as LOW, NORMAL, or HIGH. Cholesterol: The cholesterol level of the patient, categorized as NORMAL or HIGH. Na_to_K: Sodium to Potassium ratio in the patient's blood.
The target variable is the drug that each patient responded to, represented as:
Drug A Drug B Drug C Drug X Drug Y
This dataset is suitable for a multiclass classification task. One approach is to build a decision tree model using the provided features to predict the appropriate drug for a patient. The decision tree model can then be used to predict the class of an unknown patient or prescribe a drug to a new patient based on their characteristics.
This dataset is obtained from the IBM Developer Skills Network course "Machine Learning with Python" (Module 3) and is used for educational purposes.
Note: The code provided in this README is a part of the project and should be used in conjunction with the dataset and appropriate libraries.