Logistic regressing and KNeighbors Classifier

In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known.

Here we have using sklearn python lib for Logistic regressing and KNeighbors Classifier, We are testing both of classifier with iris flower dataset

With the help of metrics.accuracy_score we will the calculate the accuracy of Logistic regressing and KNeighbors Classifier for iris dataset, also here split irsh dataset for test with cross validation and then check the accuracy of both classifier.