Implementation of LogisticRegression, DecisionTreeClassifier and RandomForestClassifier on the iris dataset of sklearn datasets.
Important libraries used in this code are :
- Numpy ---> helps in working with arrays
- Pandas ---> helps to analyse data
- Matplotlib ---> helps to visualise the data
- Sklearn ---> helps to implement the ML algorithms
Method used for training and testing ---> train_test_split method of sklearn.model_selection