0.2.3

• Pandas compatibility
• Ensembles for time series
• Softer parameter checks
• Bug fixes

0.2.2

• Param change check errors fixed
• Param change raise warning
• Minor bug fixes
• Copyright

0.2.1

Introducing the computational graph backend. Version 0.2.0 implements the Learner-Transformer API, which generalizes the backend and expands the low-level API.

Version 0.2.1. includes critical a patch for model selection.

0.1.6

Merge pull request #50 from flennerhag/dev

0.1.6

0.1.5.2

• Bug fixes
• Print messages during estimation
• Clear cache

0.1.5.1

• Fixed model selection random draw argument bug

0.1.5

• Possible to set environmental variables
• multiprocessing default backend
• spawn as default start method for parallel jobs (w. multiprocessing)
• Possible to specify y as partition input in clustered subsumable partitioning
• Minor bug fixes
• Refactored backend for streamlined front-end feature development

0.1.4

Updates

• Prediction array dtype option (default=float32)
• Feature propagation
• Clustered subsemble partitioning
• No memmaps passed to estimators (only ndarray views)
• Threading as default global backend (changeable through mlens.config.BACKEND)
• Global configuration (mlens.config)
• Optional specification of temporary directory
• Scoring exception handling

0.1.3

Increased array checks, update of visualization APIs.

0.1.2

• accepts supervised transformation
• ensure training set is a view for K=2 and no preprocessing
• bug fixes model selection