Hi,
I'm getting error in sub challenge 2 main lane, although the express lane works. This is with the breast cancer dataset, the ovarian seems to work.
submission ID: 9654079
"No prediction file generated, please submit to the express lanes to debug your model!"
Best,
A.
Created by Ari Siitonen arppa99100 Dear Ari,
This is your log file:
```
Loading RNA set:
Done!
Loading cNA set:
Done!
Loading Protein names for gold set proteins
Done!
Loading RNA gene order for the genes:
Done!
Transpose RNA dataset
Dream_predictor_sub2_BREAST_final.py:90: FutureWarning: '.reindex_axis' is deprecated and will be removed in a future version. Use '.reindex' instead.
reshape_df_new = reshape_df_new.reindex_axis(sorted(select_these_genes), axis=0)
Transpose CNA dataset
Dream_predictor_sub2_BREAST_final.py:89: FutureWarning:
Passing list-likes to .loc or [] with any missing label will raise
KeyError in the future, you can use .reindex() as an alternative.
See the documentation here:
http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike
reshape_df_new = reshape_df_all.loc[select_these_genes]
Dream_predictor_sub2_BREAST_final.py:132: RuntimeWarning: divide by zero encountered in true_divide
t_RNA_dataset2 = np.hstack((t_RNA_dataset3_2, t_RNA_dataset3_2 / cna_X_train_binned))
Dream_predictor_sub2_BREAST_final.py:132: RuntimeWarning: invalid value encountered in true_divide
t_RNA_dataset2 = np.hstack((t_RNA_dataset3_2, t_RNA_dataset3_2 / cna_X_train_binned))
Done!
Predicting Protein levels using ELASTIC NET model:
Traceback (most recent call last):
File "Dream_predictor_sub2_BREAST_final.py", line 144, in
predicted_values = rf.predict(t_RNA_dataset2)
File "/usr/local/lib/python3.5/dist-packages/sklearn/utils/metaestimators.py", line 115, in
out = lambda *args, **kwargs: self.fn(obj, *args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/sklearn/model_selection/_search.py", line 467, in predict
return self.best_estimator_.predict(X)
File "/usr/local/lib/python3.5/dist-packages/sklearn/utils/metaestimators.py", line 115, in
out = lambda *args, **kwargs: self.fn(obj, *args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/sklearn/pipeline.py", line 306, in predict
Xt = transform.transform(Xt)
File "/usr/local/lib/python3.5/dist-packages/sklearn/preprocessing/data.py", line 681, in transform
estimator=self, dtype=FLOAT_DTYPES)
File "/usr/local/lib/python3.5/dist-packages/sklearn/utils/validation.py", line 453, in check_array
_assert_all_finite(array)
File "/usr/local/lib/python3.5/dist-packages/sklearn/utils/validation.py", line 44, in _assert_all_finite
" or a value too large for %r." % X.dtype)
ValueError: Input contains NaN, infinity or a value too large for dtype('float64').
```
Best,
Tom
Drop files to upload
Model passed in SC2 express lane, but failed in main lane page is loading…