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feature(MetaLabeling): replaced previous non-functional Ensembling method with Meta-labeling method available for both lvl1 and lvl2 models (#110)
* feature(MetaLabeling): added hacky prototype * fix(MetaLabeling): drop index until first valid X & y * fix(MetaLabeling): transform both X & y before feature selection * fix(MetaLabeling): got feature selection to work * fix(MetaLabeling): correct values for meta_y * feat(MetaLabeling): created predictions multiplied by bet sizes * feat(Pipeline): print out averaged result * fix(Evaluation): correctly deal with non-discretized data * fix(Pipeline): use the right column names * refactor(Pipeline): move out meta-labeling * refactor(Pipeline): complete refactoring * feat(CI): post results to PR * fix(Pipeline): use the correct filename * chore(Config): removed now redundant feature_selection flag * feat(Models): added SVC * fix(Pipeline): accidentally switched two return values * feat(Sweep): prepared sweep_meta.yaml, moved report_results() into a separate file * fix(Pipeline): wrong function name * fix(Sweep): yaml + run_sweep * fix(Sweep): typo in name * fix(Reporting): only save averaged results * feat(MetaLabeling): use optional meta-labeling step for every lvl1 models, before averaging * feat(Reporting): print out sharpe improvement in meta-labeling step * fix(Sweep): adjusted config, defaulted to good defaults * fix(Sweep): adjusted sweep
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@@ -17,8 +17,6 @@ jobs:
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- uses: iterative/setup-cml@v1
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- name: Run pytest
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shell: bash -l {0}
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# env:
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# WANDB_API_KEY: ${{ secrets.WANDB_API_KEY }}
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run: |
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pytest --junit-xml pytest.xml
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- name: Run pipeline
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@@ -37,10 +35,9 @@ jobs:
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with:
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files: pytest.xml
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# - name: Write CML report
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# env:
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# REPO_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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# run: |
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# # Post reports as comments in GitHub PRs
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# # cat results.txt >> report.md
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# # cml-send-comment report.md
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- name: Write CML report
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env:
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REPO_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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run: |
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cat results_level2.csv >> report.md
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cml-send-comment report.md
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