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Thanks for the great effort you put in this library.
As the title states, I would like to know if shap can be used to explain Learning To Rank models in the case of pairwise or listwise prediction…
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http://www.machinelearning.org/proceedings/icml2007/papers/139.pdf
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Hi,
There is an Exception during running the model, how could you solve this problem?
Traceback (most recent call last):
File "main.py", line 176, in
main(args)
File "main.py", line …
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I'm using XGBoost with lambdaMart as objective (`rank:pairwise`)
the problem with this model is the prediction of the model is a rank for each group and the score the model is giving for each item in…
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I run the SEM and my model works on 1878 cases out of 2415 because of listwise deletion. However, when I saved predicted factor scores Jamovi just pasted it in data columns regardless of which case th…
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Not root-caused yet.
Jan 14 13:45:21 compendia-prod gunicorn_supervisor.log: ERROR 2014-01-14 13:44:00,900 views 30068 139970454955776 An attempt to create an article has failed. PATH: /compendia/cr…
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这项工作的充分挖掘召回列表信息的思路太赞了。我们也准备在业务上试试。利用召回列表+曝光选择器也相当于捕捉到曝光列表的listwise信息，但依然能保留pointwise的推理方式。
我看文中使用300个召回候选，而我们业务大概400个，在serving中如何能处理这么长列表信息呢，对推理时延影响大不大？我们其他的序列特征长度也就50。难道用GPU推理加速？
谢谢
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Hello all,
I have been experimenting with the model "[learn to rank with Bert](https://github.com/tensorflow/ranking/blob/master/tensorflow_ranking/extension/tfrbert.py)". The list-wise approach wo…
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Given the features are tokenized sentences, and the targets `y_pred` are normalized rankings. A typical model accepts tokenized sentences as inputs and outputs their order/ranks.
`x`: tokenize(…
ghost updated
2 years ago
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### JASP Version
0.18.3
### Commit ID
_No response_
### JASP Module
Factor, SEM
### What analysis are you seeing the problem on?
_No response_
### What OS are you seeing the problem on?
Windo…