this is a diabetes pediction project ,based on Random forest and SVM models
this model can be used to predict the diabetes of a person
Technologies used: ->python ->pandas ->matplotlib ->seaborn ->sklearn
In this project,classification is done through random forest classifier and SVM
working of Random Forest Classifier
The random forest is a classification algorithm consisting of many decisions trees. It uses bagging and feature randomness when building each individual tree to try to create an uncorrelated forest of trees whose prediction by committee is more accurate than that of any individual tree
working of SVM
An SVM model is basically a representation of different classes in a hyperplane in multidimensional space. The hyperplane will be generated in an iterative manner by SVM so that the error can be minimized. The goal of SVM is to divide the datasets into classes to find a maximum marginal hyperplane (MMH).