Hello @vchung,
Could you please provide the log for submission 9761259 and 9761260
Thanks,
Vijay N
Created by vijay kumar narsapuram narsapvi Hi @narsapvi,
It looks like the model is again expecting Ensembl IDs as var_names. Here's a slightly abbreviated version of the full error (I ellipsed the gene names, since it seems the difference is pretty clear?):
```
File "/home/user/.local/lib/python3.8/site-packages/xgboost/core.py", line 3079, in _validate_features
raise ValueError(msg.format(self.feature_names, feature_names))
ValueError: feature_names mismatch: ['MIR1302-2HG', 'FAM138A', 'OR4F5', 'AL627309.1', 'AL627309.3', 'AL627309.2', 'AL627309.5', 'AL627309.4', 'AP006222.2', 'AL732372.1', 'OR4F29', 'AC114498.1', 'OR4F16', 'AL669831.2', 'LINC01409', 'FAM87B', 'LINC01128', 'LINC00115', 'FAM41C', 'AL645608.6', 'AL645608.2', 'AL645608.4', 'LINC02593', 'SAMD11', 'NOC2L', 'KLHL17', 'PLEKHN1', 'PERM1', 'AL645608.7', 'HES4', 'ISG15', 'AL645608.1', 'AGRN', 'AL645608.5', 'AL645608.8', 'RNF223', 'C1orf159', 'AL390719.3', 'LINC01342', 'AL390719.2', 'TTLL10-AS1', 'TTLL10', 'TNFRSF18', 'TNFRSF4', 'SDF4', 'B3GALT6', 'C1QTNF12', 'AL162741.1', 'UBE2J2', 'LINC01786', **...** , 'AC011043.2', 'AC011841.1', 'BX072566.1', 'AL354822.1', 'AL592183.1', 'AC240274.1', 'AC213203.2', 'AC213203.1', 'AC004556.3', 'AC233755.2', 'AC233755.1', 'AC136352.3', 'AC136352.2', 'AC171558.3', 'AC171558.1', 'AC133551.1', 'AC136612.1', 'AC136616.1', 'AC136616.3', 'AC136616.2', 'AC141272.1', 'AC023491.2', 'AC007325.1', 'AC007325.4', 'AC007325.2', 'NeuN_proxy'] ['ENSG00000243485', 'ENSG00000237613', 'ENSG00000186092', 'ENSG00000238009', 'ENSG00000239945', 'ENSG00000239906', 'ENSG00000241860', 'ENSG00000241599', 'ENSG00000286448', 'ENSG00000236601', 'ENSG00000284733', 'ENSG00000235146', 'ENSG00000284662', 'ENSG00000229905', 'ENSG00000237491', 'ENSG00000177757', 'ENSG00000228794', 'ENSG00000225880', 'ENSG00000230368', 'ENSG00000272438', 'ENSG00000230699', 'ENSG00000241180', 'ENSG00000223764', 'ENSG00000187634', 'ENSG00000188976', 'ENSG00000187961', 'ENSG00000187583', 'ENSG00000187642', 'ENSG00000272512', 'ENSG00000188290', 'ENSG00000187608', 'ENSG00000224969', 'ENSG00000188157', 'ENSG00000242590', 'ENSG00000273443', 'ENSG00000237330', 'ENSG00000131591', 'ENSG00000285812', 'ENSG00000223823', 'ENSG00000272141', 'ENSG00000205231', 'ENSG00000162571', 'ENSG00000186891', 'ENSG00000186827', 'ENSG00000078808', 'ENSG00000176022', 'ENSG00000184163', 'ENSG00000260179', 'ENSG00000160087', 'ENSG00000230415', 'ENSG00000162572', **...** , 'ENSG00000198692', 'ENSG00000286247', 'ENSG00000280969', 'ENSG00000254488', 'ENSG00000183146', 'ENSG00000288057', 'ENSG00000242875', 'ENSG00000234414', 'ENSG00000184991', 'ENSG00000286187', 'ENSG00000244395', 'ENSG00000242389', 'ENSG00000169807', 'ENSG00000236951', 'ENSG00000131548', 'ENSG00000169800', 'ENSG00000215560', 'ENSG00000226941', 'ENSG00000235059', 'ENSG00000131538', 'ENSG00000169789', 'ENSG00000228240', 'ENSG00000226906', 'ENSG00000183753', 'ENSG00000188120', 'ENSG00000205944', 'ENSG00000169763', 'ENSG00000280961', 'ENSG00000172352', 'ENSG00000227439', 'ENSG00000235412', 'ENSG00000183795', 'ENSG00000187191', 'ENSG00000205916', 'ENSG00000185894', 'ENSG00000228296', 'ENSG00000223641', 'ENSG00000228786', 'ENSG00000172288', 'ENSG00000231141', 'ENSG00000198888', 'ENSG00000198763', 'ENSG00000198804', 'ENSG00000198712', 'ENSG00000228253', 'ENSG00000198899', 'ENSG00000198938', 'ENSG00000198840', 'ENSG00000212907', 'ENSG00000198886', 'ENSG00000198786', 'ENSG00000198695', 'ENSG00000198727', 'ENSG00000278704', 'ENSG00000277400', 'ENSG00000274847', 'ENSG00000276256', 'ENSG00000278198', 'ENSG00000273496', 'ENSG00000277630', 'ENSG00000278384', 'ENSG00000273748', 'ENSG00000271254', 'ENSG00000277475', 'ENSG00000268674', 'ENSG00000276345', 'ENSG00000277856', 'ENSG00000275063', 'ENSG00000277666', 'ENSG00000276760', 'ENSG00000275249', 'ENSG00000274792', 'ENSG00000274175', 'ENSG00000275869', 'ENSG00000273554', 'ENSG00000278782', 'ENSG00000277761', 'ENSG00000277836', 'ENSG00000278633', 'ENSG00000276017', 'ENSG00000278817', 'ENSG00000277196']
expected ACKR4, SMU1, Z97192.2, LINC02274, **...**
training data did not have the following fields: ENSG00000241598, ENSG00000254669, ENSG00000114902, ENSG00000285492, **...**
```
As I wrote previously, the .var_names match across datasets
Best,
Kyle Hello @vchung,
We had spend quite a bit of time and our local prediction scores were competitive to the leaderboard one, I wanted to know if there a still a possibility to submit our model..! Thanks for your time in arranging this challenge. Hello @vchung
Could you please give some idea on this issue. !!
I thought the gene expression values would be present for each donor across different library prep methods. So why this is failing..!?
Hi @narsapvi ,
Here are the errors received for the two submissions (they are the same):
```
File "/home/user/.local/lib/python3.8/site-packages/xgboost/core.py", line 3079, in _validate_features
raise ValueError(msg.format(self.feature_names, feature_names))
ValueError: feature_names mismatch: ['MIR1302-2HG', 'FAM138A', 'OR4F5', 'AL627309.1', 'AL627309.3', 'AL627309.2', 'AL627309.5', 'AL627309.4', 'AP006222.2', 'AL732372.1',...
```
Edit: remove redundancy