v0.0.14

Changes

Tabular

• Complete overhaul of feature generation, major improvements to flexibility, speed, memory usage, and stability @Innixma (#584, #661).
• Revamped tabular tutorials @jwmueller (#636).
• Added fastai neural network tabular model (not used by default: requires Torch) @gradientsky (#627).
• Added LightGBM Extra Trees (LightGBM_XT) model @Innixma (#681).
• Updated model training priority for multiclass, moved neural networks to train ahead of trees @Innixma (#676).
• Added .persist_models(), .unpersist_models() methods to TabularPredictor @Innixma (#640).
• Improved neural network training time @jwmueller (#598).
• Added example for chunked inference @daveharmon (#634).
• Improved memory stability on large datasets @Innixma (#644).
• Reduced maximum memory usage of predictor.leaderboard() @Innixma (#648).
• Updated LightGBM to v3.x, resulting in ~2x speedup in most cases @Innixma (#662).
• Updated CatBoost to v0.24.x @Innixma (#664).
• Updated scikit-learn to <0.24 (from <0.23) @Innixma (#671).
• Updated pandas version to >=1.0 (from <1.0) @Innixma (#670).
• Added GPU support for CatBoost @Innixma (#682).
• Code cleanup @Innixma (#645, #665, #677, #680, #689).
• Bug Fixes @Innixma, @gradientsky, @jwmueller (#643, #666, #678, #688).

Text

• Bug Fixes @sxjscience (#651, #653).

General

• Upgraded to mxnet 1.7 (from 1.6) @sxjscience (#650).
• Updated all absolute imports to relative imports @Innixma (#637).
• Documentation Improvements @aaronkl, @rdimaio, @jwmueller (#638, #639, #679).
• Code cleanup @tirkarthi (#660).
• Bug Fixes @Innixma, @aaronkl (#674, #686).