Candidate roadmap for remainder of 2016:

Predictive models

Novelty detection using 1-class SVM  MADLIB-990
Mixed effects modeling  MADLIB-987
k-nearest neighbors (kNN)  MADLIB-927
MCMC Probit and Logit regression
Factorization machines
Gaussian Mixture Model using Expectation Maximization (EM) algorithm
Multi-layer Perceptron
Geographically Weighted Regression (GWR)

Graph

Shortest path  MADLIB-992
Standard traversal
  depth first search
  breadth first search
  topological sort
One mode projection (converting a bi-partitite graph of user-item graph to user-user or item-item graph)
Connected components
Page rank
Hierarchical graph cut
Between-ness centrality
Minimum spanning tree

Utilities

Path functions (phase 2)  MADLIB-977
Prediction metrics  MADLIB-907
Sessionization  MADLIB-909
Pivoting  MADLIB-908
Anonymization  MADLIB-911
URI tools  MADLIB-910
Stratified sampling  MADLIB-986

Usability

Expand coverage for PivotalR
Expand coverage for PMML export
Interface improvement and consistency
Implement an interface using named parameters
Python API

Performance and scalability

Work around PostgreSQL 1 GB field size limit  MADLIB-991

Platform

Support for PostgreSQL 9.5  MADLIB-944