THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
Candidate roadmap 2016:
Predictive models
- Novelty detection using 1-class SVM MADLIB-990
- Mixed effects modeling MADLIB-987
- Factorization machines
- k-nearest neighbors (kNN) MADLIB-927
- Geographically Weighted Regression (GWR)
- MCMC Probit and Logit regression
- Gaussian Mixture Model using Expectation Maximization (EM) algorithm
- Multi-layer Perceptron
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 and 9.6 MADLIB-944