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@ozguraslank ozguraslank released this 15 Apr 09:35
1.1.0
6b8cae1

What's Changed

  • [FEATURE] Added test workflow by @ozguraslank in #2
  • [ENH] Upgraded catboost to >= 1.2.3 and fixed the solver&penalty problem at Logistic Regression by @ozguraslank in #4
  • [ENH] Removed unnecessary part from license by @ozguraslank in #5
  • [OPTIMIZATION] Removed unnecessary init parts by @ugurxay in #6
  • [FEATURE] Added Time Taken Info to Trainings & Tunings by @ozguraslank in #7
  • Revised Supervised Base Module Structure (Check desc) by @ozguraslank in #8
  • Notebook Updation & tuning_size Param Remove from Model Tuning by @ozguraslank in #10
  • Verbose feature & Value Check Addition to Model Tuning by @ozguraslank in #11
  • Float rounds are adjusted & case sensitivity in eval metrics is removed by @ozguraslank in #12
  • Added Cross Validation Feature & Revised Overall Structure for It by @ozguraslank in #14
  • Improved class and function structures & Added random_state value validator by @ozguraslank in #15
  • Added MAPE and ROC-AUC evaluation metrics by @ozguraslank in #16
  • Revised cross_validation structure & added shuffle param to SupervisedBase by @ozguraslank in #17
  • Added missing MAPE indicators in func docs and functions by @ozguraslank in #18
  • Add save_model() Function, Tests, and Update Notebooks for Issue #20 by @0xkerem in #21
  • Error fix / Parameter mismatch resolved and not-used params are removed by @ozguraslank in #23
  • Optimized Unit Tests (Resolved Issue #3) by @ozguraslank in #24
  • Feature Engineering Addition by @ugurxay in #25
  • Added Smart System for quick-wide Experiments by @ozguraslank in #26
  • Improved gitignore's coverage by @ozguraslank in #27
  • Error fix / Corrected random_state variable name in repr func by @ozguraslank in #28
  • General Fixes / Init Files and Feature Engineering Module by @ozguraslank in #29
  • General Fixes / Error & Bug fixes on SupervisedBase Class by @ozguraslank in #30
  • Predict feature is added and save_model is updated by @ugurxay in #31
  • Error Fix / Eval Metrics Case handling, 'average' param configuration / Added predict_proba() function by @ozguraslank in #32
  • Improved Feature Engineering Module & Mistake Fix on Handling n_folds Param's Default Var by @ozguraslank in #34
  • Added New ML Models, Revised the currents for Issue #19 by @ozguraslank in #35
  • Error fix & Improvement / Training and evaluation issues at multiclass problems & model leaderboard improvement by @ozguraslank in #36
  • Error Fix and Improvement on Optuna and General Tuning Processes by @ozguraslank in #37
  • Revised test_ml_models unittest and removed unnecessary model import in ml_models by @ozguraslank in #38
  • Error fix and improvement at model evaluation by @ozguraslank in #39
  • General Bug Fixes and Improvements by @ozguraslank in #41
  • Fix to predict method for Classification problems by @ugurxay in #42
  • Filtered warning messages from models by @ozguraslank in #43
  • Forced root logger to be overwritten by flexml by @ozguraslank in #44
  • Improved general model structure by @ozguraslank in #45
  • Bug fix / Added 'MAPE' to reverse_signed_eval_metrics by @ozguraslank in #46
  • Error fixes on Optuna module and start_experiment of SupervisedBase by @ozguraslank in #47
  • 1.1.0b1 Release by @ozguraslank in #49
  • General fixes and improvements on 1.1.0b1 release by @ozguraslank in #51
  • General bug fixes and optimizations by @ozguraslank in #52
  • Added Codecov coverage workflow by @ozguraslank in #53
  • Added code coverage badge to README by @ozguraslank in #54
  • Disabled codecov-commenter to comment on PRs by @ozguraslank in #55
  • Improved README badges by @ozguraslank in #56
  • Improved Unit Tests by @ozguraslank in #57
  • Error raise structure revise of helper functions / if -> Raise Exception() to assert by @ozguraslank in #58
  • Reverted exception structure to previous version and improved unittest by @ozguraslank in #59
  • Change to conversion of categorical columns to string by @ugurxay in #60
  • Improved unit test coverage of the functions at flexml/helpers by @ozguraslank in #61
  • Error fix / Added 'category' dtype to categorical data check in encoders by @ozguraslank in #62
  • Added performance checks for classification and regression models by @ugurxay in #63
  • Added plot() feature by @ozguraslank in #64
  • Removed setuptools install from git workflow, added to requirements by @ozguraslank in #65
  • Enhanced repr for better table output and auto-print on object creation by @ugurxay in #66
  • Small Improvements on Quick and Wide Models and repr by @ozguraslank in #67
  • 1.1.0b2-release by @ozguraslank in #68
  • Resolved Colab Cronic Pip Version Bug by @ozguraslank in #69
  • Migrated to pyproject-toml configuration by @ozguraslank in #70
  • Released 1.1.0rc0 by @ozguraslank in #71
  • Optimized ordinal_encoder related features by @ozguraslank in #72
  • Added progress bar to model tuning and improved supervisedbase's by @ozguraslank in #73
  • Improved tune_model, progress bars and warning messages by @ozguraslank in #74
  • Released 1.1.0rc1 by @ozguraslank in #75
  • Small Improvements on UI by @ozguraslank in #76
  • Released 1.1.0rc2 in #77
  • n_jobs feature in start_experiment(), memory optimization and small fixes in #78
  • Revised Optuna tuning structure & Typing hint revise for CV param in #79
  • Added None and Object type support to plot(), Model name related mistake fixes in save_model() and predict() in #80
  • Error fix / Avoid shared pipeline state between Optuna trials during parallelization in #81
  • Released 1.1.0 in #82

New Contributors

Contributors

0xkerem, ozguraslank, and ugurxay
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