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* feat: training pipeline + tensorboard * tesnorboard forgot * chore: ml basic boilerplate * feat: naive architecture as start * eval setup * chore: parquet exporting of data * chore: updating requirements necesary * feat: separating modules and adding training logs paths * Update experiments/ml/train.py Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> * fix: new path for runs * fix: undoing ai slop code * chore: modules and reqs --------- Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
12 lines
196 B
Python
12 lines
196 B
Python
from .evals import evaluate
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from .arch import (
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XGBoostAgentClassifier,
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LightGBMAgentClassifier
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)
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__all__ =[
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'evaluate',
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'XGBoostAgentClassifier',
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'LightGBMAgentClassifier'
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]
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