The Iris flower data set or Fisher's Iris data set is a multivariate data set introduced by the British statistician and biologist Ronald Fisher in his 1936 paper. The data set consists of 50 samples from each of three species of Iris (Iris setosa, Iris virginica and Iris versicolor). Four features were measured from each sample: the length and the width of the sepals and petals, in centimetres.
Dataset - UCI Machine Learning Repository: Iris Data Set
program contain choice based code where an user is asked to enter option to observe Sepal and petal data. Also user is asked to enter choice among models :
- Logistic Regression
- KNN
- SVM
- Naive Bayes
- Decision Tree
- Random Forest Tree
Data is divided into two parts : Sepal and Petal data and each data is further divided into Train and Test data. Each model is well plotted with accuracy mentioned in the upper left corner of graph.