I like to to run the lilikoi example code with the mock data provided by the lilikoi R package, however, I am stuck at the lilikoi.machine_learning() ...

When I have categorical features in my dataset, h20 implies one-hot encoding and start the training process. When I call summary method to see the fea ...

I have a PySpark code to train an H2o DRF model. I need to save this model to disk and then load it. I can not find any document on this so I am as ...

I have hot encoded data separately (there are multiple categories under a single main variable and 30 variables). I want to know if this will effect G ...

When running xGboost Package in H2o throws Java heap space error. But when the memory is cleared manually it works fine. I often use del df del somet ...

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I am getting the following error, after trying to get most important variables with H2o Package in a classification binary problem with Rstudio. E ...

Based on H2O's documentation it would seem as though relevel('most_frequency_category') and relevel_by_frequency() should accomplish the same thing. H ...

I am using h2o automl library from python with scikit-learn wrapper to create a pipeline for training my model. I follow this example, recommended by ...

I'm wondering why h2o.performance report is different from standard definition of rmse on the test data. h2o's performance report seems to overstating ...

Here is my code: it returns: The h2o server seems to be running just fine. I am not sure how to troubleshoot. UPDATE As per suggestion below h ...

H2O document doesn't detail on these two hyper parameters. It only says these are L1 and L2 regularization parameters, with default values as 0 and 1. ...

I have a dataset of around 1M rows with a high imbalance (743 / 1072780). I am training xgboost model in h2o with the following parameters and it look ...

Hey I am using anaconda environment, and have successfully installed h20-py library and all. It's just that when I try to run h2o.init() it gives me t ...

i am using spark standalone cluster and running h2o pysparkling in it. I am unable to find the function for getting the leader feature importances. pl ...

I'm not able to understand the models generated by the H20 automl! The output is like this, for example: StackedEnsemble_AllModels_1_AutoML_1_2022080 ...

Code: Spark-submit Command: spark-submit --master spark://local:7077 --py-files sparkling-water-3.36.1.3-1-3.2/py/h2o_pysparkling_3.2-3.36.1.3- ...

I've been looking at the deviance calculation for negative binomial model in H2O (code line 580/959) and I'm struggling to reason why it is 0 when yr ...

Code: I am using spark standalone cluster 3.2.1 and try to initiate H2OContext in python file. while trying to run the script using spark-submit, i ...

im getting different output for feature importance, when I run the automl in azure, google and h2o. even though the data is same and all the features ...