Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Scala for Machine Learning

You're reading from   Scala for Machine Learning Leverage Scala and Machine Learning to construct and study systems that can learn from data

Arrow left icon
Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781783558742
Length 624 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Patrick R. Nicolas Patrick R. Nicolas
Author Profile Icon Patrick R. Nicolas
Patrick R. Nicolas
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Hello World! 3. Data Preprocessing 4. Unsupervised Learning 5. Naïve Bayes Classifiers 6. Regression and Regularization 7. Sequential Data Models 8. Kernel Models and Support Vector Machines 9. Artificial Neural Networks 10. Genetic Algorithms 11. Reinforcement Learning 12. Scalable Frameworks A. Basic Concepts Index

Kernel functions


Every machine learning model introduced in this book so far assumes that observations are represented by a feature vector of a fixed size. However, some real-world applications such as text mining or genomics do not lend themselves to this restriction. The critical element of the process of classification is to define a similarity or distance between two observations. Kernel functions allow developers to compute the similarity between observations without the need to encode them in feature vectors [8:1].

An overview

The concept of kernel methods may be a bit odd at first to a novice. Let's consider the example of the classification of proteins. Proteins have different lengths and compositions, but they do not prevent scientists from classifying them [8:2].

Note

Proteins

Proteins are polymers of amino acids joined together by peptide bonds. They are composed of a carbon atom bonded to a hydrogen atom, another amino acid, or a carboxyl group.

A protein is represented using a traditional...

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