h2o | H2O - the optimized HTTP/1 , HTTP/2 , HTTP/3 server | HTTP library
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H2O - the optimized HTTP/1, HTTP/2, HTTP/3 server
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Trending Discussions on h2o
QUESTION
I want to make sure the weights_column arguments in h2o.glm() is the same as the weights argument in glm(). To compare, I am looking at the rmse of both models using the Seatbelts dataset in R. I don't think a weight is needed in this model, but for the sake of demonstration I added one.
...ANSWER
Answered 2022-Feb-10 at 17:39With the glm your predictions are in log form. To compare them you need to use the exponential of the predictions.
QUESTION
Let's say I have the following rmd:
...ANSWER
Answered 2022-Jan-31 at 22:52Your code should look like this:
QUESTION
I am experiencing a persistent error while trying to use H2O's h2o.automl
function. I am trying to repeatedly run this model. It seems to completely fail after 5 or 10 runs.
ANSWER
Answered 2022-Jan-27 at 19:14I think I also experienced this issue, although on macOS 12.1. I tried to debug it and found out that sometimes I also get another error:
QUESTION
I am implementing my own algorithm in H2O's Java source code (under package h2o-algos
).
How can I join two frames' rows (i.e. vectors) in H2O given H2O Java methods?
For instance, given two Frame A and B
...ANSWER
Answered 2022-Jan-27 at 18:28This functionality is called "row binding", it is not exposed as an API method. It is, however, available as a Rapids expression (simple scheme-like language). You can follow this example to row-bind 2 H2O Frames: https://github.com/h2oai/h2o-3/blob/master/h2o-core/src/test/java/water/rapids/ast/prims/mungers/AstRBindTest.java#L40 In a nutshell, if you have 2 frames with keys A and B you would run water.rapids.Rapids.exec("rbind A B").getFrame()
QUESTION
h2o version: h2o-3.34.0.3 (rel-zizler)
Java version: openjdk version "15.0.2" 2021-01-19
(installed with: FROM adoptopenjdk:15-jre-openj9-focal
)
I want to build an XGBoost model using Java 15, but the same code with the same data which runs without issues on Java 14 (openjdk version "14.0.2" 2020-07-14) fails on Java 15, producing the following error messages:
...ANSWER
Answered 2022-Jan-12 at 08:48Changing Java install to FROM openjdk:15.0.2-jdk-slim
has solved the issue
QUESTION
Using the h2o package for R, I created a set of base models using AutoML with StackedEnsemble's disabled. Thus, the set of models only contains the base models that AutoML generates by default (GLM, GBM, XGBoost, DeepLearning, and DRF). Using these base models I was able to successfully train a default stacked ensemble manually using the h2o.stackedEnsemble function (i.e., a GLM with default params). I exported the model as a MOJO, shutdown the H2O cluster, restarted R, initialized a new H2O cluster, imported the stacked ensemble MOJO, and successfully generated predictions on a new validation set.
So far so good.
Next, I did the exact same thing following the exact same process, but this time I made one change: I trained the stacked ensemble with all pairwise interactions between the base models. The interactions were created automatically by feeding a list of the base model Ids to the interaction metalearner_parameter. The model appeared to train without issue and (as I described above) was able to export it as a MOJO, restart the h2o cluster, restart R, and import the MOJO. However, when I attempt to generate predictions on the same validation set I used above I get the following error:
...ANSWER
Answered 2022-Jan-06 at 14:54Unfortunately, H2O-3 doesn't currently support exporting GLM with interactions as MOJO. There's a bug that allows the GLM to be exported with interactions but the MOJO doesn't work correctly - the interactions are replaced by missing values. This should be fixed in the next release (3.36.0.2) - it will not allow to export that MOJO in the first place.
There's not much other than writing the stacked ensemble in R (base model predictions preprocessing (e.g., interaction creation) and then feeding it to the h2o.glm) that you can do. There is now an unmaintained package h2oEnsemble that might be helpful for that. You can also use another metalearner model that is more flexible, e.g., GBM.
QUESTION
My question is if Open Source H2O-3, Open Source Sparkling Water and Driverless AI are affected by CVE-2021-44228 and CVE-2021-45046.
...ANSWER
Answered 2021-Dec-19 at 00:35H2O.ai is closely tracking the vulnerabilities and publishing updates at https://www.h2o.ai/security/bulletins/h2o-2021-001/.
QUESTION
I am calculating the coordinates of a H2O using numpy.
I know that am using proper data types in the creation itself.
ANSWER
Answered 2021-Dec-15 at 09:20Adding the dtype=object
specification
QUESTION
I have 2 docker containers running my webapp and my machine learning application, both using h2o. Initially, I had both calling h2o.init() and pointing to the same IP:PORT, consequently a single h2o cluster with one node was initialized.
Consider that I have a model already trained and now I'm training a second one. During this training process, if the webapp made a call to the h2o cluster (e.g., requesting a predict from the first model), it would kill the training process (error message bellow), which was unintended. I tried setting a different port for each app but the same situation kept ocurring. I don't understand why since I thought that by setting two different ports, two indepentent clusters would be initialized, and, therefore, two jobs could run simultaneously.
Error message
...ANSWER
Answered 2021-Sep-20 at 18:17If you want to launch H2O via CLI with 3 independent nodes, then give them different names:
-name H2O_CLUSTER_NAME_1
-name H2O_CLUSTER_NAME_2
-name H2O_CLUSTER_NAME_3
If you try to give theme the same name, they will try to form a cluster. See here.
QUESTION
I'm working with a chemical dataset and I was wondering about the smartest way to do the following thing. My dataset looks something like this:
...ANSWER
Answered 2021-Jul-23 at 13:25How about this:
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