Learning Apache Mahout Classification: Build and personalize your own classifiers using Apache Mahout PDF
Preview Learning Apache Mahout Classification: Build and personalize your own classifiers using Apache Mahout
www.it-ebooks.info www.it-ebooks.info Learning Apache Mahout Classification www.it-ebooks.info Table of Contents Learning Apache Mahout Classification Credits About the Author About the Reviewers www.PacktPub.com Support files, eBooks, discount offers, and more Why subscribe? Free access for Packt account holders Preface What this book covers What you need for this book Who this book is for Conventions Reader feedback Customer support Downloading the example code Downloading the color images of this book Errata Piracy Questions 1. Classification in Data Analysis Introducing the classification Application of the classification system Working of the classification system Classification algorithms Model evaluation techniques The confusion matrix The Receiver Operating Characteristics (ROC) graph Area under the ROC curve www.it-ebooks.info The entropy matrix Summary 2. Apache Mahout Introducing Apache Mahout Algorithms supported in Mahout Reasons for Mahout being a good choice for classification Installing Mahout Building Mahout from source using Maven Installing Maven Building Mahout code Setting up a development environment using Eclipse Setting up Mahout for a Windows user Summary 3. Learning Logistic Regression / SGD Using Mahout Introducing regression Understanding linear regression Cost function Gradient descent Logistic regression Stochastic Gradient Descent Using Mahout for logistic 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 www.it-ebooks.info 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 Steps to use the Random forest algorithm in Mahout Summary 7. Learning Multilayer Perceptron Using Mahout Neural network and neurons Multilayer Perceptron MLP implementation in Mahout Using Mahout for MLP Steps to use the MLP algorithm in Mahout Summary 8. Mahout Changes in the Upcoming Release Mahout new changes Mahout Scala and Spark bindings Apache Spark Using Mahout’s Spark shell 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 The ASF e-mail dataset Classifiers tuning www.it-ebooks.info Summary Index www.it-ebooks.info www.it-ebooks.info Learning Apache Mahout Classification www.it-ebooks.info www.it-ebooks.info
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