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! 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
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Arrow up icon
GO TO TOP
Regression Analysis with Python

You're reading from   Regression Analysis with Python Discover everything you need to know about the art of regression analysis with Python, and change how you view data

Arrow left icon
Product type Paperback
Published in Feb 2016
Publisher
ISBN-13 9781785286315
Length 312 pages
Edition 1st Edition
Languages
Tools
Concepts
Arrow right icon
Authors (2):
Arrow left icon
Luca Massaron Luca Massaron
Author Profile Icon Luca Massaron
Luca Massaron
Alberto Boschetti Alberto Boschetti
Author Profile Icon Alberto Boschetti
Alberto Boschetti
Arrow right icon
View More author details
Toc

Table of Contents (11) Chapters Close

Preface 1. Regression – The Workhorse of Data Science 2. Approaching Simple Linear Regression FREE CHAPTER 3. Multiple Regression in Action 4. Logistic Regression 5. Data Preparation 6. Achieving Generalization 7. Online and Batch Learning 8. Advanced Regression Methods 9. Real-world Applications for Regression Models Index

Defining a classification problem


Although the name Logistic Regression suggests a regression operation, the goal of Logistic Regression is classification. In a very rigorous world such as statistics, why is this technique ambiguously named? Simple, the name is not wrong at all, and it makes perfect sense: it just requires a bit of an introduction and investigation. After that you'll fully understand why it's named Logistic Regression, and you'll no longer think that it's a wrong name.

First, let's introduce what a classification problem is, what a classifier is, how it operates, and what its output is.

In the previous chapter, we presented regression as the operation of estimating a continuous value in a target variable; mathematically speaking, the predicted variable is a real number in the range (−∞, +∞). Classification, instead, predicts a class, that is, an index in a finite set of classes. The simplest case is named binary classification, and the output is typically a Boolean value ...

lock icon The rest of the chapter is locked
Visually different images
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Regression Analysis with Python
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 €18.99/month. Cancel anytime
Modal Close icon
Modal Close icon