Apache MLlib
Apache Spark MLlib provides a powerful computational environment for ML. It provides a distributed architecture on a large-scale basis, allowing one to run ML models more quickly and efficiently. That's not all; it is open source with a growing and active community continuously working to improve and provide the latest features. It provides a scalable implementation of the popular ML algorithms. It includes algorithms for the following:
- Classification: Logistic regression, linear support vector machine, Naive Bayes
- Regression: Generalized linear regression
- Collaborative filtering: Alternating least square
- Clustering: K-means
- Decomposition: Singular value decomposition and principal component analysis
It has proved to be faster than Hadoop MapReduce. We can write applications in Java, Scala, R, or Python. It can also be easily integrated with TensorFlow.
Regression in MLlib
Spark MLlib has built-in methods for regression. To be able to use the built-in methods of Spark, you will have...
