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Hi Team, I'm using XGBoost4J to do online inference, however, I encounter an issue that when executing predict method in multiple thread environments, the native code will fail with SIGSEGV.
Runtim…
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When trying to slice a booster, it will not accept all formats that python would otherwise accept, and it's not clear what exactly it considers acceptable ranges - for example, if the step is not equa…
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There does not seem to be a support for missing values currently.
For example dealing with the 'Age' feature in the Titanic dataset:
```
import pandas as pd
import sklearn
import catboost
impo…
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I am working on a tricky classification problem that has unbalanced classes (10 to 1 ratio), with around 200,000 instances and approximately 10 features.
I managed to get reasonable performance using…
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Since I am stumbling over this for the nth time:
`predict_type` and `predict_types` are easy to confuse (and it happens to me quite a lot).
- `predict_type`: The concrete type of the prediction th…
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Hi,
I might have missed it, but I fail to find some info on the preprocessing of data.
Is there some documentation on that part?
What columns are being used in the end?
How are they encoded?
Ca…
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I get the following error:
`**Error in benchmark(learners, fuelTask, holdout) : Assertion on 'design' failed: Must be of type 'data.frame', not 'list'.**`
When trying to benchmark the kNN, Rand…
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:mag:**case exploration**
a new potential dataset, student performance https://archive.ics.uci.edu/ml/datasets/student+performance
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When i run with own data set,I get the following error:
AttributeError Traceback (most recent call last)
in
4 feature='sex',
5 feature_name='Gender…
szz01 updated
3 years ago
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{code:java}
>data = h2o.importFile("https://s3.amazonaws.com/h2o-public-test-data/smalldata/gbm_test/titanic.csv")
>data$survived = as.factor(data$survived)
> model = h2o.xgboost(x = 4:7,y = 2,tr…