Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Machine Learning with scikit-learn Quick Start Guide

You're reading from   Machine Learning with scikit-learn Quick Start Guide Classification, regression, and clustering techniques in Python

Arrow left icon
Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781789343700
Length 172 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Kevin Jolly Kevin Jolly
Author Profile Icon Kevin Jolly
Kevin Jolly
Arrow right icon
View More author details
Toc

Table of Contents (10) Chapters Close

Preface 1. Introducing Machine Learning with scikit-learn FREE CHAPTER 2. Predicting Categories with K-Nearest Neighbors 3. Predicting Categories with Logistic Regression 4. Predicting Categories with Naive Bayes and SVMs 5. Predicting Numeric Outcomes with Linear Regression 6. Classification and Regression with Trees 7. Clustering Data with Unsupervised Machine Learning 8. Performance Evaluation Methods 9. Other Books You May Enjoy

Implementing the k-NN algorithm using scikit-learn

In the following section, we will implement the first version of the k-NN algorithm and assess its initial accuracy. When implementing machine learning algorithms using scikit-learn, it is always a good practice to implement algorithms without fine-tuning or optimizing any of the associated parameters first in order to evaluate how well it performs.

In the following section, you will learn how to do the following:

  • Split your data into training and test sets
  • Implement the first version of the algorithm on the data
  • Evaluate the accuracy of your model using a k-NN score

Splitting the data into training and test sets

The idea of training and test sets is fundamental to every...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image