Closed t-soehngen closed 1 year ago
Replacing 2 values in the maize dataset (e.g. maize_fields.tsv) with NA reproduces the error
Hi, thanks for reporting the bug and also adding some details on how to reproduce it! That was super helpful.
Seems like we didn't expect one feature datasets to have NaN values, but I have fixed it so now it shouldn't be throwing any errors. If you come across another exception or have any other question, please feel free to open another issue. 🙂
The new version of MOVE (1.4.6) is up. ⬆️
I'm currently training MOVE on proteomics data in combination with lots of categorical data (with a few missing values). My input data is structured as instructed (1 Feature/File, missing values = NA).
When MOVE tries to calculate the score during reconstruction tuning, it struggles with the missing values since num_features has the original length (including masked entries) but y_true and y_pred have lengths n - n_masked. Excluding all categorical features containing missing values results in a successful run. What is the correct way to fix that error? analysis\metrics.py
The Error thrown is below: