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

View More author details

The K-Nearest Neighbors Classifier

Now that we have our training and testing data, it is time to prepare our classifier to perform k-nearest neighbor classification. After being introduced to the k-nearest neighbor algorithm, we will use scikit-learn to perform classification.

Introducing the K-Nearest Neighbors Algorithm (KNN)

The goal of classification algorithms is to divide data so that we can determine which data points belong to which group.

Suppose that a set of classified points is given to us. Our task is to determine which class a new data point belongs to.

In order to train a k-nearest neighbor classifier (also referred to as KNN), we need to provide the corresponding class for each observation on the training set, that is, which group it belongs to. The goal of the algorithm is to find the relevant relationship or patterns between the features that will lead to this class. The k-nearest neighbors algorithm is based on a proximity measure that calculates the...

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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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You're reading from The Applied Artificial Intelligence Workshop

The K-Nearest Neighbors Classifier

Introducing the K-Nearest Neighbors Algorithm (KNN)

Unlock this book and the full library FREE for 7 days

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