ignore warnings
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@ -554,7 +554,9 @@ class Hyperopt:
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# Perform a cross-validation estimate of the coefficient of determination using
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# Perform a cross-validation estimate of the coefficient of determination using
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# the cross_validation module using all CPUs available on the machine
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# the cross_validation module using all CPUs available on the machine
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# K = 5 # folds
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# K = 5 # folds
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R2 = cross_val_score(res.models[-1], X=res.x_iters, y=res.func_vals, cv=5, n_jobs=jobs).mean()
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with warnings.catch_warnings():
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warnings.simplefilter("ignore")
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R2 = cross_val_score(res.models[-1], X=res.x_iters, y=res.func_vals, cv=5, n_jobs=jobs).mean()
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print(f'R2: {R2}')
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print(f'R2: {R2}')
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R2 = R2 if R2 > -5 else -5
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R2 = R2 if R2 > -5 else -5
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self.mse_list.append(R2)
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self.mse_list.append(R2)
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