Recent Releases of galaxy-ml
galaxy-ml - Release v0.10.0
Changes
- Updates scikit-learn to 1.1.x, tensorflow to v2.10.x, xgboost to 1.7.x.
- Add github workflow to test tools using docker container as dependencies.
- Restructure search algos in searchCV tool.
- Serialize html repr for models.
- Test utils and tools in python 3.9.
Bug Fixes
- Fix some tool lint errors
- Fix lots of flake8 errors but ignoring F401,F821, I100 and W503.
- HTML
Published by qiagu over 3 years ago
galaxy-ml - V0.9.0
Changes
- Updates scikit-learn to v0.24.x, tensorflow to v2.4.x, xgboost to v1.3.x, mlxtend to v0.17.x, skrebate to v.62, imbalanced-learn to v0.8.x and so on.
- Makes loadmodel and savemodel util methods in kerasgalaxymodel module.
- Refactors
_SafePicklerand moves it fromutilstomodel_persist. - Refactors
dump_model_to_h5andload_model_from_h5to dynamically save and load xgboost and tensorflow models. - Replaces pickled models with
h5mlmmodels in all tools.
Bug Fixes
- HTML
Published by qiagu almost 5 years ago
galaxy-ml - V0.8.3
Changes
- Makes image deep learning tool.
- Adds
BayesSearchCVin searchcv tool. - Makes new metric
spearman_correlation_scoreand its corresponding scorer. - Adds a new parameter
n_stratification_binstoOrderedKFoldandRepeatedOrderedKFold. - Adds multi-output classification support for
KerasGClassificationandKerasGBactchClassifier.
Bug Fixes
- Fixes dependencies issue, numpy < 1.19, h5py < 3, tensorflow-estimator==1.15.1.
- Fixes various test issues.
- HTML
Published by qiagu about 5 years ago
galaxy-ml - V0.8.0
Version 0.8.0 / tool_main: 1.0.8.0 / keras: 0.5.0 (12-10-2019)
New Features
- Adds circleci config for both api and tool tests.
- Adds traintestsplit tool which supports shufflesplit, stratifiedshufflesplit, groupshufflesplit and orderedtarget split.
- Adds fittedmodeleval tool.
- Refactors binarize target estimators. There are a lot of improvements. One of them is that the estimator family now support most sklearn scorers.
- Adds clean_params in utils
- Adds cvresults outputs for nested inner CV and unfitted searchCV object from searchCV tool.
- Adds keras training and evaluation tool.
- Adds support of decision_function for binarize target classifiers.
- Adds matplotlib svg format option in
ml_visualization_extool. - Adds 'sklearn.ensemble.HistGradientBoostingClassifier' and 'sklearn.ensemble.HistGradientBoostingRegressor'
- Adds new regression scorer
max_error. - Upgade scikit-lean to v0.21.3, mlxtend to v0.17.0, imbalanced-learn to v0.5.0, keras to v2.3.1 and tensorflow to v1.15.0.
Changes
- Replaces all generators'
fitwithset_processing_attrs. - Raises ValueError instead of [0, 1] normalization when predictions from
BinarizeTargetRegressorgo out of range. - Refactors
iraps_classifiermodule. Binarize target estimators do the same prediction as the wrapped estimator. A delicatedpredict_scoreis made to work with binarize scorers. - Changes precision-recall curve and ROC curve to take headers and upgrade plotly to v4.3.0 in mlvisualizationex tool
- Changes to dynamic output of pipeline or final main estimator
Bug Fixes
- Fixes randomstate error in `predict_generator`.
- Fixes stale path issue by replacing relative paths with full paths.
- HTML
Published by qiagu over 6 years ago
galaxy-ml - V0.7.13
Version 0.7.13 / tool_main: 1.0.7.12 / stacking: 0.2.0 / keras: 0.4.2 (09-17-2019)
New Features
- Adds searchcv tools to output
weightsfor deep learning models. - Makes
KerasGBatchClassifier.evalueto support multi-class and multi-label classification problem. - Adds parameter
verbosein KerasG models to output device placement. - Adds
metricsin keras model building tools. - Makes
train_test_evaltool. - Makes
GenomicVariantBatchGenerator. - Makes
model_predictiontool to supportvcffile type. - Adds plotly plotting tool facility for
feature_importances,learning_curve,pr_curveandroc_curve. - Adds
_predict_generatorto output y_true together with prediction results. - Adds support of
return_train_scoreforKerasGBatchClassifierin gridsearchcv. - Adds
ml_visualization.xmltool support many plots.
Changes
- Changes dependency
tensorflowtotensorflow-gpu. - Moves all tools to folder
tools. - Makes
sklearn.preprocessing.Imputerdeprecated. - Updates dependencies in
requrements.txt. - Refactor
keras_model_configtool by grouping layer key words arguments. - Refactor the
preprocessors.pyinto folder structure.
Bug Fixes
- Fixes
KerasGBatchClassifierdoesn't work with callbacks. - Fixes
GenomicIntervalBatchGeneratordoesn't work in nested model validation. - Fixes
GenomicIntervalBatchGeneratorfailed for sequences in blacklist matches.
- HTML
Published by qiagu over 6 years ago