ABSTRACT
This chapter discusses the likelihood of patients being readmitted to the hospital after discharge, and how the knowledge of drugs taken by the patient and medical data can help in making these predictions. It explains the basic concepts of entropy-based feature selection. The chapter evaluates the algorithms and flow of PySpark-based algorithms, and reports concentrations of features. Frequent work has been carried out in the field of feature selection. The accurate prediction model needs to identify the relevant feature. Entropy is an essential approach used to identify the uncertainty of the predicted variables. The entropy formula for decision entropy is formulated on the basis of if the entropy_features based on the target variable. Different works based on entropy are obtained in the proposed work decision entropy is computed to improve the predictive accuracy. The readmission prediction is of significant importance for both hospitals and patients.
