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Python Machine Learning By Example

You're reading from   Python Machine Learning By Example The easiest way to get into machine learning

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781783553112
Length 254 pages
Edition 1st Edition
Languages
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Authors (2):
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Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Author Profile Icon Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (9) Chapters Close

Preface 1. Getting Started with Python and Machine Learning 2. Exploring the 20 Newsgroups Dataset with Text Analysis Algorithms FREE CHAPTER 3. Spam Email Detection with Naive Bayes 4. News Topic Classification with Support Vector Machine 5. Click-Through Prediction with Tree-Based Algorithms 6. Click-Through Prediction with Logistic Regression 7. Stock Price Prediction with Regression Algorithms 8. Best Practices

Predicting stock price with regression algorithms

In theory, we can apply regression techniques in predicting prices of a particular stock. However, it is difficult to ensure that the stock we pick is suitable enough for learning purposes—its price should follow some learnable patterns and it should not be affected by unprecedented instances or irregular events. Hence, we herein will be focusing on one of the most popular stock indexes to better illustrate and generalize our price regression approach.

Let's first cover what an index is. A stock index is a statistical measure of the value of a portion of the overall stock market. An index includes several stocks that are diverse enough to represent a section of the whole market. And the price of an index is typically computed as the weighted average of the prices of selected stocks.

The Dow Jones Industrial Average (DJIA) is one of the longest established...

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