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Block: from datasetsforecast.losses import mse, mae, rmse from datasetsforecast.evaluation import accuracy
evaluation_df = accuracy(cv_df, [mse, mae, rmse], agg_by=['unique_id']) evaluation_df['best_model'] = evaluation_df.drop(columns=['metric', 'unique_id']).idxmin(axis=1) evaluation_df.head()
The following line could have been inserted here: from neuralforecast.losses.pytorch import MSE, MAE, RMSE, Accuracy
But then there is a problem with the Accuracy class, it doesn't have a similar method.
ModuleNotFoundError Traceback (most recent call last) Cell In[55], line 1 ----> 1 from datasetsforecast.losses import mse, mae, rmse 2 from datasetsforecast.evaluation import accuracy 4 evaluation_df = accuracy(cv_df, [mse, mae, rmse], agg_by=['unique_id'])
ModuleNotFoundError: No module named 'datasetsforecast.losses'
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The text was updated successfully, but these errors were encountered:
Fixed by 2.0 release
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Description
Description
Block:
from datasetsforecast.losses import mse, mae, rmse
from datasetsforecast.evaluation import accuracy
evaluation_df = accuracy(cv_df, [mse, mae, rmse], agg_by=['unique_id'])
evaluation_df['best_model'] = evaluation_df.drop(columns=['metric', 'unique_id']).idxmin(axis=1)
evaluation_df.head()
The following line could have been inserted here:
from neuralforecast.losses.pytorch import MSE, MAE, RMSE, Accuracy
But then there is a problem with the Accuracy class, it doesn't have a similar method.
ModuleNotFoundError Traceback (most recent call last)
Cell In[55], line 1
----> 1 from datasetsforecast.losses import mse, mae, rmse
2 from datasetsforecast.evaluation import accuracy
4 evaluation_df = accuracy(cv_df, [mse, mae, rmse], agg_by=['unique_id'])
ModuleNotFoundError: No module named 'datasetsforecast.losses'
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The text was updated successfully, but these errors were encountered: