v1.1.6 release

The main bugs fixed:

1. #82
2. A previous bug: after getting an attribute of a LazyLoadingEstimator object, the model was not auto-dumped. This is now fixed.

v1.1.5 release

This is a large update

Features:

1. The major changes are that the AdaSTEM class now supports duckdb and parquet file path as input, this allow the user to pass in large dataset without duplicating the pandas dataframe cross the processors when working with n_jobs>1 parallel computing. See the new Jupyter notebooks for details. #76
2. The lazy loading is no longer realized by theLazyLoadingEnsemble class. Instead, it is realized by LazyLoadingEstimator. This allow the model to be dumped once its training/prediction is finished, and we don't need to accumulate the models (hence, memory) until the training is finished for the whole ensemble. This will largely reduce the memory use. See the new Jupyter notebooks for details. #77
3. n_jobs > ensemble_folds are no longer supported for user-end clarity. Those jobs are paralleled by ensemble folds so n_jobs > ensemble_folds is meaning less. We do not want to mislead users to think that a 10-ensemble model will be trained faster using n_jobs=20 compared to n_jobs=10.
4. These features will not be available in SphereAdaSTEM due to the negligible user market and the negligible advantages. #75

Major bugs fixed:

1. Previously the models are stored in self.model_dict dynamically during the parallel ensemble training process, which means the dictionary is being altered during this process. However, we ask for a self as input argument for the ensemble-level training function serialization. This is not ideal since the object being serialized should not be changing. This is fixed by assigning the model_dict to self after all trainings are finished.
2. Also fixed #74

v1.1

This is a big release for the completion of JOSS review🎉.

Main change:

• Add spherical indexing system SphereAdaSTEM
• Add multiprocessing

v1.0.9.1

Main changes:

• Update random jitter method of quadtree.
• Update the splitting algorithm. Stop splitting if any of the child grid contain less than certain amount of samples.
• Update gif plotting method. under_grey.
• Update multiprocessing for training.

stemflow-v1.0.0

Formal release of stemflow version 1.0.0

stemflow-v0.0.27

stemflow-v0.0.27

Use hurdle model as AdaSTEM model for all demos.

stemflow-v0.0.22

stemflow release version 0.0.22