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You're reading from Apache Spark 2.x Machine Learning Cookbook

Product typeBook

Published inSep 2017

Reading LevelIntermediate

PublisherPackt

ISBN-139781783551606

Edition1st Edition

Languages

Scala

Tools

Apache Spark

Concepts

Machine Learning

Authors (5):

Mohammed Guller

Siamak Amirghodsi

Shuen Mei

Meenakshi Rajendran

Broderick Hall

View More author details

Linear regression API with Lasso and L-BFGS in Spark 2.0

In this recipe, we will demonstrate the use of Spark 2.0's LinearRegression() API to showcase a unified/parameterized API to tackle the linear in a comprehensive capable of extension without backward-compatibility issues of an RDD-based named API. We show how to use the setSolver() to set the optimization method to first-order memory-efficient L-BFGS, which can deal with numerous amount of parameters (that is, especially in sparse configuration) with ease.

Note

In this recipe, the .setSolver() is set to lbgfs, which makes the L-BFGS (see RDD-based regression for more detail) the selected optimization method. The .setElasticNetParam() is not set, so the default of 0 remains in effect, which makes this a Lasso regression.

How to do it...

We use a housing dataset from the UCI machine library depository.

Download the entire data set from the following URLs:
- https://archive.ics.uci.edu/ml/datasets/Housing
- https://archive.ics.uci.edu/ml/machine...

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Apache Spark 2.x Machine Learning Cookbook

Published in: Sep 2017Publisher: PacktISBN-13: 9781783551606

Authors (5)

Mohammed Guller

Author of Big Data Analytics with Spark - http://www.apress.com/9781484209653
Read more about Mohammed Guller

Siamak Amirghodsi

Siamak Amirghodsi (Sammy) is interested in building advanced technical teams, executive management, Spark, Hadoop, big data analytics, AI, deep learning nets, TensorFlow, cognitive models, swarm algorithms, real-time streaming systems, quantum computing, financial risk management, trading signal discovery, econometrics, long-term financial cycles, IoT, blockchain, probabilistic graphical models, cryptography, and NLP.
Read more about Siamak Amirghodsi

Shuen Mei

Shuen Mei is a big data analytic platforms expert with 15+ years of experience in designing, building, and executing large-scale, enterprise-distributed financial systems with mission-critical low-latency requirements. He is certified in the Apache Spark, Cloudera Big Data platform, including Developer, Admin, and HBase. He is also a certified AWS solutions architect with emphasis on peta-byte range real-time data platform systems.
Read more about Shuen Mei

Meenakshi Rajendran

Meenakshi Rajendran is experienced in the end-to-end delivery of data analytics and data science products for leading financial institutions. Meenakshi holds a master's degree in business administration and is a certified PMP with over 13 years of experience in global software delivery environments. Her areas of research and interest are Apache Spark, cloud, regulatory data governance, machine learning, Cassandra, and managing global data teams at scale.
Read more about Meenakshi Rajendran

Broderick Hall

Broderick Hall is a hands-on big data analytics expert and holds a masters degree in computer science with 20 years of experience in designing and developing complex enterprise-wide software applications with real-time and regulatory requirements at a global scale. He is a deep learning early adopter and is currently working on a large-scale cloud-based data platform with deep learning net augmentation.
Read more about Broderick Hall

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You're reading from Apache Spark 2.x Machine Learning Cookbook

Linear regression API with Lasso and L-BFGS in Spark 2.0

Note

How to do it...

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Authors (5)

Hands-On Big Data Analytics with PySpark

Machine Learning with Spark

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