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24 lines
755 B
Python
24 lines
755 B
Python
# sklearn compatible models for agent detection
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from sklearn.base import BaseEstimator, ClassifierMixin
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from procesing.context import PipelineContext
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from typing import Any, Optional, Tuple
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from abc import ABC, abstractmethod
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import xgboost as xgb
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import lightgbm as lgb
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import numpy as np
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import pandas as pd
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TASK = 'classification'
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LABELS = ['human', 'agent']
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class WeakClassifier(BaseEstimator, ClassifierMixin, ABC):
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# a simple contrastive machine learning model
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# this model should learn to distinguish between human and agent behavior
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# using a weakly supervised approach and contrastive learning + augmentation
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#
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def __init__(self, **kwargs):
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super().__init__()
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self.model = None
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self.kwargs = kwargs
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