metrics中的fitness函数 #16229
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@lyC121 the fitness function prioritizes mAP metrics because they provide a comprehensive measure of model performance across different IoU thresholds, which is often more indicative of overall effectiveness than precision and recall alone. |
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一下是metrics中关于fitness函数如下
def fitness(self):
"""Model fitness as a weighted combination of metrics."""
w = [0.0, 0.0, 0.1, 0.9] # weights for [P, R, [email protected], [email protected]:0.95]
return (np.array(self.mean_results()) * w).sum()
为什么最后的best.pt的权重主要是在[email protected]和[email protected]:0.95,而P和R的权重都为0###
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