Classification-of-Iris-Data-using-Machine-learning methods developed in Python.

This is an small machine learning project done using python and various libraries such as numpy, scipy, scikit-learn, pandas and matplotlib for classifiying the Iris plant data and its prediction using four attributes such as Sepal length, Sepal width, Petal length and Petal width. along with classes it belong to such as Iris-setosa, Iris-virginica, Iris-versicolor. I imported data directly from the UCI Machine Learning Repository.

Process:

1. Prepare the data
2. select a model for classification.
3. Use validation methods and confusion Matrix for prediction and finding erros made - We use 10-fold cross-validation method and we split the data into 80% for training and 20% for validation.
4. Select the best model by calculating the accuracy score of each models.(We have taken various Linear and non-linear models i.e, Logisitic regression, Linear Discriminant Analysis,KNN, CART, NB, SVM)