56 lines
1.5 KiB
Python
56 lines
1.5 KiB
Python
import numpy as np
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def from_name(err_name):
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assert err_name in ERROR_NAMES, f"unknown error {err_name}"
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callable_error = globals()[err_name]
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return callable_error
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# def f1(prev):
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# # https://github.com/dice-group/gerbil/wiki/Precision,-Recall-and-F1-measure
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# if prev[0] == 0 and prev[1] == 0 and prev[2] == 0:
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# return 1.0
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# elif prev[0] == 0 and prev[1] > 0 and prev[2] == 0:
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# return 0.0
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# elif prev[0] == 0 and prev[1] == 0 and prev[2] > 0:
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# return float('NaN')
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# else:
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# recall = prev[0] / (prev[0] + prev[1])
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# precision = prev[0] / (prev[0] + prev[2])
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# return 2 * (precision * recall) / (precision + recall)
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def f1(prev):
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den = (2 * prev[3]) + prev[1] + prev[2]
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if den == 0:
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return 0.0
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else:
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return (2 * prev[3]) / den
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def f1e(prev):
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return 1 - f1(prev)
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def acc(prev: np.ndarray) -> float:
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return (prev[0] + prev[3]) / np.sum(prev)
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def accd(true_prevs: np.ndarray, estim_prevs: np.ndarray) -> np.ndarray:
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vacc = np.vectorize(acc, signature="(m)->()")
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a_tp = vacc(true_prevs)
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a_ep = vacc(estim_prevs)
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return np.abs(a_tp - a_ep)
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def maccd(true_prevs: np.ndarray, estim_prevs: np.ndarray) -> float:
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return accd(true_prevs, estim_prevs).mean()
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ACCURACY_ERROR = {maccd}
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ACCURACY_ERROR_SINGLE = {accd}
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ACCURACY_ERROR_NAMES = {func.__name__ for func in ACCURACY_ERROR}
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ACCURACY_ERROR_SINGLE_NAMES = {func.__name__ for func in ACCURACY_ERROR_SINGLE}
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ERROR_NAMES = ACCURACY_ERROR_NAMES | ACCURACY_ERROR_SINGLE_NAMES
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