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https://github.com/webclinic017/drift.git
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Mark Aron Szulyovszky
567cd5e9f0
* refactor(Evaluate): print out accuracy, f1, etc. for the final & meta predictions, separated out evaluation step * fix(Linter): ran * fix(Tests): syntax change * fix(Inference): runs now again * fix(Linter): ran
43 lines
954 B
Python
43 lines
954 B
Python
import pandas as pd
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from dataclasses import dataclass
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from typing import Optional, Dict
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PredictionsSeries = pd.Series
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WeightsSeries = pd.Series
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ProbabilitiesDataFrame = pd.DataFrame
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Stats = Dict[str, float]
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ModelOverTime = pd.Series
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TransformationsOverTime = list[pd.Series]
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@dataclass
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class BaseTrainingOutcome:
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model_id: str
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predictions: PredictionsSeries
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probabilities: ProbabilitiesDataFrame
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model_over_time: ModelOverTime
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@dataclass
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class TrainingOutcome(BaseTrainingOutcome):
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transformations: TransformationsOverTime
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stats: Optional[Stats]
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@dataclass
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class BetSizingWithMetaOutcome(TrainingOutcome):
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weights: WeightsSeries
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@dataclass
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class PipelineOutcome:
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directional_training: TrainingOutcome
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bet_sizing: BetSizingWithMetaOutcome
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def get_output_weights(self) -> WeightsSeries:
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return self.bet_sizing.weights
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def get_output_stats(self) -> Stats:
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return self.bet_sizing.stats
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