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I'm trying to convert a model that has been saved in .sav in onnx format. The model is a VotingClassifier (XGBOOST and NaiveBayes). I got the error
`Traceback (most recent call last):
File "/mn…
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I'm using the following code to generate Python code from a XGBoost (`bst` is a previously trained XGBoost object)
```
temp_file = "temp.json"
bst.save_model(temp_file)
skclf = xgb.XGBClassifier…
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Hi,
Is there are a way to get metrics values for a given set of parameters in nfold_cv() function? or is there any other way to tune hyperparameters of xgboost model in XGBoost.jl.
Thank you,
…
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We use spark to generate libsvm file, then use python sklearn to load it and xgboost to train and save model, finaly use leaves load it and predict.
the predict result was total incorrect between py…
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Hi!
I want to use mljar for binary classification (category1+category2).
The parameters I am passing to AutoML are the following:
```
automl = AutoML(results_path=str(model_directory),
…
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There is a problem with boolean condition when I want to import a model of XGBOOSTClassifier
I trained a XGBOOSTClassifier with some booleans features (with true and false and not 1 and 0 as possib…
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I have observed a significant performance regression in XGBoost version 1.7 when using the fit method with evaluation sets in sklearn estimators. The issue appears to have been introduced by [this com…
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### Description
Tried the diabetes tutorial and ran this:
```
flytectl demo start
cd examples/pima_diabetes
pyflyte run --remote pima_diabetes/diabetes.py diabetes_xgboost_model # as usually prac…
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The use of Gradient Boosting Machines algorithms ( XGBoost) or Neural Networks can enhance the performance of the model .
Please assign me ,to work on this issue.
4ryn updated
3 months ago
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Hi Kassem,
I like this project.
I recommend replacing XGBoost with CatBoost. CatBoost handles categorical features more efficiently and often requires less hyperparameter tuning. For more infor…