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Big Data Analytics with Java

You're reading from   Big Data Analytics with Java Data analysis, visualization & machine learning techniques

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787288980
Length 418 pages
Edition 1st Edition
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Author (1):
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RAJAT MEHTA RAJAT MEHTA
Author Profile Icon RAJAT MEHTA
RAJAT MEHTA
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Table of Contents (15) Chapters Close

Preface 1. Big Data Analytics with Java FREE CHAPTER 2. First Steps in Data Analysis 3. Data Visualization 4. Basics of Machine Learning 5. Regression on Big Data 6. Naive Bayes and Sentiment Analysis 7. Decision Trees 8. Ensembling on Big Data 9. Recommendation Systems 10. Clustering and Customer Segmentation on Big Data 11. Massive Graphs on Big Data 12. Real-Time Analytics on Big Data 13. Deep Learning Using Big Data Index

Flower species classification using multi-Layer perceptrons

This is a simple hello world-style program for performing classification using multi-layer perceptrons. For this, we will be using the famous Iris dataset, which can be downloaded from the UCI Machine Learning Repository at https://archive.ics.uci.edu/ml/datasets/Iris. This dataset has four types of datapoints, shown as follows:

Attribute name

Attribute description

Petal Length

Petal length in cm

Petal Width

Petal width in cm

Sepal Length

Sepal length in cm

Sepal Width

Sepal width in cm

Class

The type of iris flower that is Iris Setosa, Iris Versicolour, Iris Virginica

This is a simple dataset with three types of Iris classes, as mentioned in the table.

From the perspective of our neural network of perceptrons, we will be using the multi-perceptron algorithm bundled inside the spark ml library and will demonstrate how you can club it with the Spark-provided pipeline API for the easy manipulation of the machine...

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