spindro / GINN

Graph Imputation Neural Network
http://ispac.diet.uniroma1.it/
Apache License 2.0
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To get the result of mae and rmse #7

Open joey00113 opened 2 years ago

joey00113 commented 2 years ago

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!

spindro commented 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.

joey00113 commented 2 years ago

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.

joey00113 commented 2 years ago

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Zjh152 commented 1 year ago

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So how to solve this problem?

joey00113 commented 1 year ago

这是来自QQ邮箱的自动回复邮件。您好,您的邮件我已收到,我会尽快处理并且给您回复,祝您生活愉快。