”Classication and Prediction of Heart Disease Risk in Data Mining Techniques”
Keywords:
Classification Techniques, decision Tree algorithmic program, cardiopathy, kNN, Naïve mathematician, Neural Network, Risk levelAbstract
currently a days, health un-wellness square measure increasing day by day because of life vogue,
hereditary. Especially, heart disease has become additional common recently .i.e. lifetime of folks is in danger. Every
individual has completely different values for force per unit area, sterol and vital sign. But in step with medically welltried results the traditional values of force per unit area is 120/90, sterol is and vital sign is seventy two. This paper
offers the survey concerning completely different classification techniques used for predicting the chance level of
every person supported age, gender, force per unit area, sterol, pulse rate. The patient risk level is classed
mistreatment data mining classification techniques like Naïve mathematician, KNN, call Tree algorithmic program,
and Neural Network. etc., Accuracy of the chance level is high once mistreatment additional variety of attributes.
