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F# for Machine Learning Essentials

You're reading from   F# for Machine Learning Essentials Get up and running with machine learning with F# in a fun and functional way

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Product type Paperback
Published in Feb 2016
Publisher
ISBN-13 9781783989348
Length 194 pages
Edition 1st Edition
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Author (1):
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Sudipta Mukherjee Sudipta Mukherjee
Author Profile Icon Sudipta Mukherjee
Sudipta Mukherjee
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Table of Contents (9) Chapters Close

Preface 1. Introduction to Machine Learning FREE CHAPTER 2. Linear Regression 3. Classification Techniques 4. Information Retrieval 5. Collaborative Filtering 6. Sentiment Analysis 7. Anomaly Detection Index

Identifying praise or criticism with sentiment orientation


The evaluative character of a word is called its semantic orientation. Positive semantic orientation indicates praise (for example, honest, intrepid) and negative semantic orientation indicates criticism (for example, disturbing, superfluous). Semantic orientation varies in both direction (positive or negative) and degree (mild to strong). An automated system for measuring semantic orientation will have its application in text classification, text filtering, tracking opinions in online discussions, analysis of survey responses, and automated chat systems (chatbots).

Semantic Orientation (SO) is used to determine whether a particular phrase is praising or criticizing someone or something. Turney and Littman proposed an algorithm for determining that using SO.

If the SO of the phrase is positive then the phrase is thought to have a positive sentiment; in other words, the phrase is said to be praising. Otherwise, if the SO value of the...

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