Iris-Project

This is a Machine learning Model used to distinguish between different Iris .It uses Iris-Dataset imported from sklearn.dataset.
It uses four Features to differentiate between targets :-

1. Sepal Length(cm)
2. Sepal Width(cm)
3. Petal Length(cm)
4. Petal Width (cm)

It distinguishes Three targets namely:-
1. Setosa 2. Versicolor 3. Varginica
It uses the train_test_split function to split the available dataset into the Training(75%) and Testing(25%) model.
Algorithm Used:-
KNeighborClassifier(kNN)
Number of neighbors =3
It used Pandas Dataframe and mglearn Library to plot and visualize the relationship between two of four features of the dataset.