You're reading from The Applied Artificial Intelligence Workshop

Product typeBook

Published inJul 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781800205819

Edition1st Edition

Languages

Python

Tools

Jupyter

Concepts

Artificial Intelligence

Authors (3):

Anthony So

William So

Zsolt Nagy

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Decision Trees

A decision tree has leaves, branches, and nodes. Nodes are where a decision is made. A decision tree consists of rules that we use to formulate a decision (or prediction) on the prediction of a data point.

Every node of the decision tree represents a feature, while every edge coming out of an internal node represents a possible value or a possible interval of values of the tree. Each leaf of the tree represents a label value of the tree.

This may sound complicated, but let's look at an application of this.

Suppose we have a dataset with the following features and the response variable is determining whether a person is creditworthy or not:

Figure 4.1: Sample dataset to formulate the rules

A decision tree, remember, is just a group of rules. Looking at the dataset in Figure 4.1, we can come up with the following rules:

All people with house loans are determined as creditworthy.
If debtors are employed and studying, then...

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The Applied Artificial Intelligence Workshop

Published in: Jul 2020Publisher: PacktISBN-13: 9781800205819

Authors (3)

Anthony So

Anthony So is a renowned leader in data science. He has extensive experience in solving complex business problems using advanced analytics and AI in different industries including financial services, media, and telecommunications. He is currently the chief data officer of one of the most innovative fintech start-ups. He is also the author of several best-selling books on data science, machine learning, and deep learning. He has won multiple prizes at several hackathon competitions, such as Unearthed, GovHack, and Pepper Money. Anthony holds two master's degrees, one in computer science and the other in data science and innovation.
Read more about Anthony So

William So

William So is a Data Scientist with both a strong academic background and extensive professional experience. He is currently the Head of Data Science at Douugh and also a Lecturer for Master of Data Science and Innovation at the University of Technology Sydney. During his career, he successfully covered the end-end spectrum of data analytics from ML to Business Intelligence helping stakeholders derive valuable insights and achieve amazing results that benefits the business. William is a co-author of the "The Applied Artificial Intelligence Workshop" published by Packt.
Read more about William So

Zsolt Nagy

Zsolt Nagy is an engineering manager in an ad tech company heavy on data science. After acquiring his MSc in inference on ontologies, he used AI mainly for analyzing online poker strategies to aid professional poker players in decision making. After the poker boom ended, he put extra effort into building a T-shaped profile in leadership and software engineering.
Read more about Zsolt Nagy

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Decision Trees

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