Heart Disease Prediction-based on Conventional KNN and Tuned-Hyper Parameters of KNN: An Insight

The proposed research work aims to predict the heart disease-based on conventional KNN and tuned-hyper parameters of KNN for enhanced performance. Initially, the conventional KNN Model is adopted to determine and predict the heart diseases with respect to the dataset collected from Kaggle Domain. Later, the hyper-parameters are tuned for determining the prediction performance on the same dataset. The various parameters identified for tuning the performance includes, the parameter grid, score and cross validation. Experimental observations depict that the hyper-tuned KNNs algorithm has enhanced performance than the conventional KNN model in terms of prediction accuracy.