v1.0.3.20200727 (2020-07-28)
Implemented enhancements:
Fixed bugs:
- Check dfcleaner corr value works with negatively cross-correlated sampes #316
Closed issues:
Merged pull requests:
- specify requirements for time being #299 (ardunn)
- update docs with updated matbench info #282 (ardunn)
- remove .needs_oxi check in AutoFeaturizer #280 (ardunn)
- Add testing instructions to CONTRIBUTNG.md #271 (janosh)
- add ability to prevent a feature cache overwrite on transform #269 (ardunn)
- Make name of new column with predictions appended to dataframe configurable #267 (janosh)
v1.0.3.20191111 (2019-11-12)
Implemented enhancements:
- Look into caching via nearest neighbors #194
Fixed bugs:
- The .git folder is absolutely enormous. #189
Closed issues:
- Consider integrating with python dask #237
v1.0.2.20191110 (2019-11-11)
Merged pull requests:
v1.0.1.20191110 (2019-11-11)
v1.0.0.20191110 (2019-11-10)
Implemented enhancements:
- Enforce a code style #208
Fixed bugs:
- Add CI for python 3.6 #259
Closed issues:
- Fix common segfaults #260
- TPOT segmentation fault #257
- TypeError: can't pickle _thread.RLock objects when saving a pipe #253
Merged pull requests:
- add CI for 3.6 #263 (ardunn)
- Tpot downgrade #261 (ardunn)
- Add pyproject.toml to config black line length #258 (janosh)
- Dev improvements #256 (ardunn)
- Logging redux #255 (ardunn)
- temporary workaround to avoid crashes on saving, until logging is redone #254 (ardunn)
- Code style enforcement #245 (janosh)
v2019.10.14 (2019-10-15)
Implemented enhancements:
- More pipeline diagnostics #239
- add dependabot #236
- Add .from_preset method to MatPipe #232
- Change or add to digest to make it easier to read #221
- Featurizer sets can be more easily rewritten as dataclasses #209
- rm /tutorials and add to matminer_examples #205
- Add warning when large numbers of samples imputed/handled #199
Fixed bugs:
- Code docs need overhaul #244
- Pipeline save/load with TPOT backend doesn't attrs in intuitive way #241
- MatPipe.load should refuse to load from class instance #234
- Automatminer save/load needs more robust test #231
- Add warning for mismatched versions of automatminer on save/load #230
- Fix requirements #229
- Autofeaturizer caching needs to use matminer utils, not pd.json #226
- initialize_logger has confusing arguments #204
Closed issues:
- Reassign pipe logger #242
- MatPipe save/load does not work on TPOTAdaptor pipelines #235
- Add ability to MatPipe to suppress internal warnings #233
- Make it easier to ignore entire columns but keep them in returned df #228
- Benchdev needs a workflow for predicting properties #227
- add function to matpipe to output pipeline as simple script? #224
- VERSION FileNotFoundError on import #223
- Add automatminer citation to all matbench datasets #218
- Docs suck #216
- Rewrite analytics to MatPipe #186
Merged pull requests:
- serialize backend and test improvements #246 (ardunn)
- refactor setting loggers #243 (janosh)
- Add support for pipeline digest in JSON and YAML format #238 (janosh)
v2019.9.11 (2019-09-11)
v2019.9.12 (2019-09-11)
Closed issues:
- benchdev needs to be updated with newest matbench v0.1 names #222
- benchdev infrastructure changes #220
v2019.08.07_beta (2019-08-08)
v2019.08.07_betaK (2019-08-08)
Closed issues:
- fix failing tests #215
- remove target from predict? #214
- Cannot rebuild docs? #213
- Consider replacing XGBoost with Catboost #195
- TPOT will, on occasion, randomly fail #181
- Make an autokeras adaptor #147
- Look at skater rule based models as a solution for small datasets #145
v2019.05.14_beta0 (2019-05-15)
Closed issues:
- Update xgboost version to 0.80 #210
- featurization takes too much ram #206
- setup.py imports automatminer #202
- Include a (basic) neural network separate from NNAdaptor #197
- Metaselector needs a rework #149
Merged pull requests:
- Use MultiSURF* instead of MultiSURF #207 (utf)
- fix versioning #203 (ardunn)
- make DFTransformer inherit BaseEstimator #201 (Qi-max)
v2019.03.27_beta (2019-03-27)
Merged pull requests:
v2019.03.26b0 (2019-03-27)
Closed issues:
- matpipe benchmark does not work with StratifiedKFold #191
- Change TPOT default optimization metric to MAE? #190
- PCA fails if matrix is large and n_features > n_samples #183
- Add "powerups" to presets #180
- General problem: Featurization takes too long! #179
- DataCleaner na_method is sloppy #178
- Autofeaturizer logging is annoying #177
- Autofeaturizer may run redundant conversions as many as 3 times #176
- Add circleci test for 3.7 #175
- Logger should append to existing logs, not overwrite it #174
- Analytics tests should run whether or not they are on circleci #169
- Real docs + more thorough example #167
- Add option to control tree and correlation-based FeatureReducer params #162
- Use MEGNet/CGCNN as backend? #156
- Need more featurizers implemented in matminer/automatminer #143
- Outlier detection as a preprocessing step #135
- Look into FunctionFeaturizer #134
- Analysis class needs to be beefed up with something actually useful #105
- Analysis should produce summary and visualization as file #57
Merged pull requests:
- Documentation is completed #198 (samysspace)
- Edits1 #196 (ardunn)
- changing base classes #187 (ardunn)
v2019.02.03_beta (2019-02-03)
v2019.02.02_beta (2019-02-02)
Closed issues:
- Nose ---> unittest #171
- Fix benchmarking #170
- Should add to PyPi #168
- An adapter to run a single model #165
- Add option to remove specific features #159
- Analytics module needs tests #133
Merged pull requests:
- Update codacy and circleCI configs #173 (utf)
- Add optional to manually keep/remove features #172 (utf)
v2019.01.26_beta (2019-01-26)
Closed issues:
- MatPipe code needs revamp #166
- Implement nested CV for pipeline benchmarking #163
- CircleCI + package reqs needs update #150
v2019.01.25_beta (2019-01-26)
Closed issues:
- List-like test_spec behavior broken in benchmark function #161
- Add random_state option to benchmark function #160
- Autofeaturizer needs ability to use custom column names #148
- Add jarvis to AllFeaturizers #144
- Empty logger made anytime MatPipe imported #141
- removing correlated features doesn't work for classification targets #140
- Oxidation states guessed twice #138
- Look into using NestedCV for automl, and whether it would be a good idea or not #130
- Add a very simple example #108
- Add another study comparison with matbench #65
- Add a profiler to DataframeTransformer #56
Merged pull requests:
- Added Examples Folder and MSE Example #158 (ADA110)
- Analytics Module Tests #157 (ADA110)
- (WIP) Custom Column Names #152 (ADA110)
- Better handling of adding oxidation states to large structures. #142 (utf)
2018.12.11_beta (2018-12-12)
Closed issues:
- No module named 'automatminer.featurize' #146
- metaselection needs error handling, or screening beforehand #139
- Add logging warning level option to Matpipe object. #136
- Add ability to ensemble top models in tpot #111
- Make dataset test set #107
- Consider adaptor classes for other backends #100
- Using skater for analysis #95
- Tpot defaults need investigation and modification #79
- Add more featurizers to AllFeaturizers #60
Merged pull requests:
- Add logging level option to pipeline object #137 (utf)
- Basic Analytics Tools #132 (Doppe1g4nger)
- dev_scripts draft for evaluation + various fixes #131 (ardunn)
v2018.11.16-beta (2018-11-17)
v2018.11.2-beta (2018-11-17)
Closed issues:
- MatPipe cannot be serialized #124
- MatPipe needs tests #118
- DataCleaner needs scaling #115
- Logger problems #114
- Remove temp fix of CompositionToOxidComposition with next matminer #113
- Tpot tests need to be redone #109
- Top level classes should be able to serialize all pipeline info to json #102
- Top level class methods need work #97
- Tests need coverage assessment #83
- Dataset storage needs improvement #80
Merged pull requests:
- update benchmark on matpipe and update test #129 (ardunn)
- Add matpipe tests, digest, and ability to save and load pipes #127 (ardunn)
- MatPipe improvements + tpot tests #126 (ardunn)
- Refactor mslearn to use matminer for its dataset needs #125 (Doppe1g4nger)
- remove conversion override and fix log typos #123 (ardunn)
- quick update verbosity of adaptor #122 (ardunn)
- big ol refactor + matpipe updates #121 (ardunn)
- make metaselection part of AutoFeaturizer #120 (Qi-max)
- Fix pipeline logger #119 (utf)
v2018.11.2-alpha (2018-11-02)
Closed issues:
- Logger needed #103
- Heuristic based featurizer selection #99
- ++robustness and usefulness of featurizer sets #98
- Convert preprocessing modele into 2 separate operations #96
- Adding/converting .fit/.transform/.predict methods #92
- Further package structure suggestions #88
- Rename AutoML segment of pipeline to better reflect package use #87
- Plan - WIP #85
- TestAllFeaturizers will break whenever a new featurizer is added #82
- test_tpot hard to maintain with tpot version update #73
- Dimensionality reduction #61
- matminer issue: MaximumPackingEfficiency error #59
- set mpid as index if available in load_* functions #58
- Castelli is missing structure or the doc is incorrect #54
- Testing takes unacceptably long times #49
- zhou gaps formula can't be converted to composition #38
- Model Selection Methodology #33
- normalize preprocess for the future use of pipeline #20
- find a way to obtain feature_cols list and target_col easily #19
- load_* functions should ensure all numeric columns #16
- load_mp should return other quantities #15
- all formula columns in load_* funcs should return Composition objects #14
- What is MatbenchError? #11
Merged pull requests:
- Adding top level class + bugfixes #117 (ardunn)
- change logging default and show example #116 (ardunn)
- a base to start from #112 (ardunn)
- Matbench wide logger #110 (utf)
- Improve metalearning for automatically filter featurizers #106 (Qi-max)
- add cv docs + citations and implementors methods #104 (albalu)
- add TreeBasedFeatureReduction + tests #101 (albalu)
- Adding top level class skeleton and jarvis dataset #94 (ardunn)
- Update dataset loading utilities to use new function #93 (Doppe1g4nger)
- organize preprocess just a bit #91 (albalu)
- Improved testing of AllFeaturizers class #90 (utf)
- Update conversions to use conversion featurizers #89 (utf)
- make subpackages and their importing consistent #86 (albalu)
- consistent naming #84 (albalu)
- Organize file structure, add a dataset + more #81 (ardunn)
- Code cleanup on tpot_utils #78 (Doppe1g4nger)
- Cleanup is_greater_better function #76 (Doppe1g4nger)
- fix logger issue duplicated in notebooks #75 (albalu)
- Add classifier/regressor config_dicts for customizing pipeline operators #74 (Qi-max)
- Split + improve existing glass datasets and add a new dataset #72 (Qi-max)
- Change default for max_na_frac, add notebook #71 (ardunn)
* This Changelog was automatically generated by github_changelog_generator