Error in CRLI for clustering

[LinglongQian]

the testing stage

crli_results = crli.predict(dataset_for_testing)
crli_prediction = crli_results["clustering"]

--> [2]crli_results = crli.predict(dataset_for_testing)
--> [426]clustering = self.model.kmeans.fit_predict(clustering_latent)
--> [175]raise ValueError(msg_err)

ValueError: Input X contains NaN.
KMeans does not accept missing values encoded as NaN natively. For supervised learning, you might want to consider sklearn.ensemble.HistGradientBoostingClassifier and Regressor which accept missing values encoded as NaNs natively. Alternatively, it is possible to preprocess the data, for instance by using an imputer transformer in a pipeline or drop samples with missing values.

[WenjieDu]

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[github-actions]

This issue had no activity for 14 days. It will be closed in 1 week unless there is some new activity. Is this issue already resolved?

[WenjieDu]

I'm closing this issue for now because we cannot reproduce this error. I assume this may be caused by the unstable performance of CRLI.

Reopening this issue is welcome if error reproducing is possible.