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Changelog

0.25.0.dev0 (yyyy-mm-dd)

0.24.0 (2023-08-22)

  • Add flake8 to the CI.
  • Use the metalearning weights when all actions have equals UCB.
  • Use the mean adtm values as probabilities for the patterns.

0.23.0 (2022-07-04)

  • Create a compressed Meta-learning DB.
  • Add support for LUPI tasks.
  • Fix CI.

0.22.0 (2022-05-20)

  • Send the path (to save model weights) as hyperparameter.
  • Remove warning about the absolute paths.
  • Show error from scoring process.
  • Use raw datasets for the examples.
  • Add datasets for the examples.
  • Add observations to the installation procedure.
  • Update documentation.

0.21.1 (2022-03-29)

  • Unlock d3m dependencies.
  • Update documentation.

0.21.0 (2022-03-22)

  • Add 'resource_folder' parameter to the API.
  • Remove unused data reader module.
  • Add more Jupyter Notebook examples.

0.20.0 (2022-03-21)

  • Add alpha-containers package.
  • Restructure repository and implement a new API.
  • Read version from file.
  • Update instructions for releases.
  • Move dependencies from setup.py to requirements.txt.

0.11.0 (2022-02-18)

  • Use D3MPORT env variable.
  • Added instructions for releases.
  • Relax requirements.
  • Disable reuse port in GRPC.

0.10 (2022-02-11)

  • Implemented the PyPI version (lightweight)
  • Added support to to blacklist and whitelist primitives
  • Added support to save and load pipelines.
  • Use timeout_run parameter to score pipelines during search.
  • Use the AutoML RPC utils for encoding GRPC pipelines.
  • Implemented the method SaveFittedSolution of the AutoML RPC API.
  • Restructure packages (rename d3m_ta2_nyu to alphad3m).
  • Expose outputs of each step within the pipeline.
  • Build automatically the grammar from the metalearning database.
  • Calculate primitive correlations.
  • Added scripts for running on SLURM/Singularity.

Version v2020.12.08 (internal)

  • Added encoders (text, datetime, etc.) to the grammar.
  • Added timeout for pipeline execution (during search).
  • Added support to expouse outputs of the pipeline steps.
  • Added support for ROC AUC metric.
  • Renamed repository to AlphaD3M.

Version v2020.07.24 (internal)

  • Added support for video data type.
  • Improved support for semi-supervised task through SemisupervisedClassificationBuilder class.
  • Updated license to Apache-2.0.

Version v2020.06.21 (internal)

  • Added support for clustering problems.
  • Created NN inputs for AlphaD3M from the metalearningDB #46 !49
  • Changed the structure of the preprocessing module. Added text and datetime encoders.
  • Updated to core package v2020.5.18 and TA2-TA3 API v2020.6.2.

Version v2020.02.16 (internal)

Submission for Winter evaluation.

  • Added data profiler to the workflow. #39 !47
  • Added support for LUPI problems.
  • Added encoders to the search by AlphaD3M.
  • Updated to core package v2020.1.9 and TA2-TA3 API v2020.2.11.

Version v2019.12.8 (internal)

Submission for December dry-run.

  • Added different tasks to the grammar. #35 !42
  • Updated sampling strategy. #30 #32
  • Added templates to external process.
  • Updated to core package v2019.11.10 and TA2-TA3 API v2020.12.4.
  • Changed internal versioning to CalVer format.

0.9 (2019-06-18)

Submission for June dry-run.

  • Added standard Reference Runtime to execute pipelines
  • Added data sampling strategies and priorization of some D3M primitives
  • Added RANK metric (and corresponding RANKING evaluation method) for TA2-only evaluation
  • Added rank_solutions_limit parameter in SearchSolutions which allows request both searching and ranking at the same time
  • Updated TA3-TA2 API functions: ListPrimitivesRequest, SearchSolutions and ScoreSolution
  • Updated to core package v2019.6.7 and TA2-TA3 API v2019.6.11

0.8.1 (2018-08-08)

Re-submission for 2018 Summer evaluation after Gov team mixup on TA1 library freeze

  • Finish implementing gRPC server (which we were initially planning to do before TA2 and TA3 deadlines)
  • Use correct base image, mandated by Gov
  • Added an 8-minute timeout to ScoreJob (some primitives freeze)
  • Only report scored pipelines to TA3, don't inform them of created-not-yet-scored (or broken) pipelines

0.8 (2018-08-01)

First submission for 2018 Summer evaluation (original deadline).

  • Build from common jpl/docker_images/complete images
  • Use d3m package to load dataset, remove MIT-LL's d3mds.py
  • Added eval.sh entrypoint to support Data Machine's eval protocol
  • Updated gRPC to v2018.7.7
  • Training/testing is now independent of Session, which only handles searching
  • Add a timeout on AlphaD3M
  • Do tuning after top pipelines have been trained and written out (then train the tuned pipelines)
  • Use KFoldDatasetSplit primitive to do cross-validation splits

0.7 (2018-06-06)

  • Added AlphaD3M pipeline generation
  • Enabled huperparameter tuning with SMAC
  • Added the Job class for the run queue
  • Introduced own multiprocessing code using sockets and avoiding fork issues

0.6.2 (2018-03-13)

Bug fixes.

0.6.1 (2018-02-08)

Bug fixes.

0.6 (2018-02-07)

Bug fixes.

0.5 (2018-01-31)

Version submitted to NIST for 2018 January evaluation.

  • Added hyperparameter tuning with SMAC. Disabled, does not work
  • Raise the number of pipelines by using one of 3 imputers, one of 2 encoder
  • Updated gRPC to v2017.12.20

0.4 (2018-01-16)

January dry-run version.

  • Removed VisTrails
  • Moved from Python 2.7 to Python 3.6
  • Renamed package from d3m_ta2_vistrails to d3m_ta2_nyu
  • Use d3mds.py from MIT-LL to load dataset
  • Use some D3M primitives, in addition to "native" scikit-learn: KNNImputation and Encoder from ISI's dsbox

0.3 (2017-12-07)

  • Added CI
  • Updated gRPC to v2017.10.10

0.2 (2017-10-05)

Version submitted to NIST for 2017 Fall TA3 evaluation.

  • Improvement to data-reading code
  • Create directories

0.1 (2017-10-02)

Version submitted to NIST for 2017 Fall TA2 evaluation.

  • Using gRPC protocol v2017.9.11
  • Custom data-reading code, identifies column types, does PCA for image data

0.0 (2017-08-24)

Start of project, using VisTrails for workflow representation and execution.