Research on Prediction Model Based on R Language Algorithm and Random Search—Taking the Death Risk Prediction of Heart Failure as an Example
This paper uses Simple Random Sampling method,and divides the training set and the test set in a 7:3 ratio.Based on this training set,SVM,BP Neural Network,Decision Tree,Random Forest,Adaboost Algorithm,and Weighted K-nearest Neighbors classification models are established,and the test set is used to test the effect of the Heart Failure death risk prediction model.Accuracy,Recall Ratio,Precision Rate,Kappa coefficient,F1 score and other evaluation indexes are used to evaluate the prediction effect of various models after optimization.Finally,the BP Neural Network is selected as the best disease risk prediction model,which provides some reference opinions for clinical diagnosis of Heart Failure medical research.
Heart FailureRandom Searchprediction modeloptimum model
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