Coders Packet

Prediction using Decision Tree Algorithm

By Vimal Kumar Verma

For the ‘Iris’ dataset, I have create the Decision Tree classifier(in Python) and visualize it graphically.(Prediction using Decision Tree Algorithm)

The decision tree is an important algorithm for predictive modelling and can be used to visually and explicitly represent decisions. It is a graphical representation that makes use of branching methodology to exemplify all possible outcomes based on certain conditions. In decision tree internal node represents a test on the attribute, branch depicts the outcome and leaf represents decision made after computing attribute.

Decision Trees have great use in financing for option pricing and are used by banks to classify loan applicant by probability of their default payment. It is also used widely in data science libraries in Python and R.

This packet is written in python and uses following Python libraries:

1. NumPy-1.16.4

2. pandas-0.24.2

3.Seaborn-0.9.0

4.scikit-learn-0.21.2

5. Matplotlib-3.1.0

At the end of this packet you will clearly see that Iris dataset is classified and see it as graphically.

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