Ashish Gupta - Learning Apache Mahout Classification [2015, PDF, ENG] torrent

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Learning Apache Mahout Classification

Год: 2015
Автор: Ashish Gupta
Издательство: Packt Publishing
ISBN: 9781783554959
Язык: Английский
Формат: PDF
Качество: Изначально компьютерное (eBook)
Интерактивное оглавление: Нет
Количество страниц: 130
Описание: This book is a practical guide that explains the classification algorithms provided in Apache Mahout with the help of actual examples. Starting with the introduction of classification and model evaluation techniques, we will explore Apache Mahout and learn why it is a good choice for classification.
Next, you will learn about different classification algorithms and models such as the Naïve Bayes algorithm, the Hidden Markov Model, and so on.
Finally, along with the examples that assist you in the creation of models, this book helps you to build a mail classification system that can be produced as soon as it is developed. After reading this book, you will be able to understand the concept of classification and the various algorithms along with the art of building your own classifiers.
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[spoiler="Оглавление"]
1: Classification in Data Analysis
Introducing the classification
Classification algorithms
Model evaluation techniques
Summary

2: Apache Mahout
Introducing Apache Mahout
Algorithms supported in Mahout
Reasons for Mahout being a good choice for classification
Installing Mahout
Summary

3: Learning Logistic Regression / SGD Using Mahout
Introducing regression
Summary

4: Learning the Naïve Bayes Classification Using Mahout
Introducing conditional probability and the Bayes rule
Understanding the Naïve Bayes algorithm
Understanding the terms used in text classification
Using the Naïve Bayes algorithm in Apache Mahout
Summary

5: Learning the Hidden Markov Model Using Mahout
Deterministic and nondeterministic patterns
The Markov process
Introducing the Hidden Markov Model
Using Mahout for the Hidden Markov Model
Summary

6: Learning Random Forest Using Mahout
Decision tree
Random forest
Using Mahout for Random forest
Summary

7: Learning Multilayer Perceptron Using Mahout
Neural network and neurons
Multilayer Perceptron
MLP implementation in Mahout
Using Mahout for MLP
Summary

8: Mahout Changes in the Upcoming Release
Mahout new changes
Apache Spark
H2O platform integration
Summary

9: Building an E-mail Classification System Using Apache Mahout
Spam e-mail dataset
Creating the model using the Assassin dataset
Program to use a classifier model
Testing the program
Second use case as an exercise
Classifiers tuning
Summary
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