SHAP error

[wangqiankun0201]

ValueError: Columns of dataframes passed to fit() and transform() differ:

• f
• e
• d
• c
• b
• a

• 0
• 1
• 2
• 3
• 4
• 5

[anuragg1209]

Hi @wangqiankun0201

Thanks for reporting this issue. Could you please provide more details or code to reproduce the error? Also, it seems like the column mismatch might be resolved by reindexing the dataframe. Can you try that and see if it helps?

Something like: df_transform = df_transform.reindex(columns=df_fit.columns)

Thanks!

[wangqiankun0201]

X_train.columns = ["0", "1", "2", "3", "4", "5"]
X_test.columns = ["0", "1", "2", "3", "4", "5"]
By adding the above code, the problem has been solved. I would also like to ask if it took me a long time to calculate SHAP, is it normal？

[wangqiankun0201]

shap_values = interpretability.shap.parallel_permutation_shap(
reg,
X_test,
n_jobs=-1
)
Why does the above code report an error:
ValueError: Number of processes must be at least 1.
I use google's colab

[LeoGrin]

Could you show what X_test looks like? It seems that this error message can appear for weird datasets like empty or 1 row datasets (nalepae/pandarallel#141).

[wangqiankun0201]

0	1	2	3	4	5

1016 | 18.4 | 6 | 280 | 0.5 | 15
1422 | 18.4 | 6 | 120 | 0.5 | 10
1016 | 18.4 | 7 | 120 | 0.5 | 15
1016 | 18.4 | 2 | 120 | 0.5 | 15
1016 | 18.4 | 5 | 120 | 0.5 | 0
... | ... | ... | ... | ... | ...
1016 | 26.4 | 6 | 120 | 0.5 | 15
1016 | 18.4 | 6 | 60 | 0.5 | 10
1016 | 18.4 | 6 | 120 | 0.4 | 0
1016 | 18.4 | 6 | 160 | 0.5 | 0
1016 | 18.4 | 6 | 180 | 0.5 | 5
My X_test look like this

[oscarkey]

hey @wangqiankun0201 , sorry for the delay in replying. Are you still facing this error with the latest version of TabPFN and its dependencies? If so, could you attach a minimal script which reproduces the error?