Open joey00113 opened 2 years ago
Hi! MAE and RMSE can be computed on artificially induced missing values of course. The function imputation_accuracy takes 3 arguments, the original dataset, the imputed one and the mask indicating where are the missing values. This mask is the second output of degrade_dataset.
Thanks!I knew what the three parameters refer to. The main problem is the dimension of imputed dataset varies from that of the original dataset.It seems that some one-hot codes were added to the imputed dataset. Could you tell me how to make the imputed dataset have the same dimension and format as the original dataset? Only in this condition that the calculation of mae and rmse is meaningful.
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So how to solve this problem?
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Hi,I want to know the result of mae and rsme after new dataset was added to the test. In utils.py you define a function named imputation_accuracy but you don‘t use it in the example using heart dataset . When I try to use this function in mydataset to get mae,I got some error!Could you tell me the usage of the function to get the result of mae and rmse?Thanks!