Some potential roadmap items for 2018+ below.  For more details please see the JIRAs. 

Predictive models

• Multi-class SVM  Unable to render Jira issues macro, execution error.
• Mixed effects modeling  Unable to render Jira issues macro, execution error.
• Gradient boosted machines
• Gaussian Mixture Model using Expectation Maximization (EM) algorithm  Unable to render Jira issues macro, execution error.
• Hierarchical clustering
• Deep learning

Graph

• Personalized PageRank  Unable to render Jira issues macro, execution error.
• Betweenness centrality  Unable to render Jira issues macro, execution error.
• Graph cut  Unable to render Jira issues macro, execution error.
• Triangle counting  Unable to render Jira issues macro, execution error.
• Minimum spanning tree
• Eigenvector centrality  Unable to render Jira issues macro, execution error.

Utilities

• Balanced datasets  Unable to render Jira issues macro, execution error.
  Summary - add more statistics  Unable to render Jira issues macro, execution error.
• Anonymization  MADLIB-911
• URI tools  MADLIB-910

Usability

• Expand coverage for PivotalR
• Expand coverage for PMML export??? (or perhaps switch to PFA???)
• Interface improvement and consistency for 2.0 release (does not need to be backward compatible)
• Implement an interface using named parameters
• Python API

Performance and scalability

• Work around PostgreSQL 1 GB field size limit  MADLIB-991
• GPU support
• Improve decision tree and random forest performance for run-time and memory usage MADLIB-1057 MADLIB-976

Platform

• Support for PostgreSQL 9.5 and 9.6  MADLIB-944
• Tensorflow support, or another deep learning framework