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Hi all,
Since I have a large dataset to predict, I'm using `train_time_limit` as a setting to fit automl as below (as introduced in #65 ). However, it does not seem to work as the `automl.best_conf…
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Per comment below, this is now supported, but needs to be documented.
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## Summary
Add statistics to the plot from a dataset, its labels and predictions
## Motivation
lgb.create_tree_digraph and plot_tree are really great to visualize the tree, but without the st…
wil70 updated
2 months ago
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If parameter tree_learner in my model.txt is serial, can each tree in this model be predicted using multiple threads?
when I test it, I found only one thread with 100% CPU usage, all the otheer threa…
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## 💥 Proposal
Hello, I am Siddhant Dutta - I am a GSSOC'23 Contributor. This is my resume - [Resume](https://drive.google.com/file/d/1iRPv-76FDxEyo-7QdmxDp3le7DEabK-Q/view?usp=sharing)
# Introdu…
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- [ ] have an examples folder
- [ ] basic regressor
- [ ] basic classifier
- [ ] advanced options
- [ ] same, but in an ipython notebook
- [ ] use a large dataset (https://www.kaggle.co…
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## Description
We've run into an issue where identical input data produces different feature importance if the column order is different. This happens even with `feature_fraction: 1.0, 'deterministic…
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## Description
I am working on a project where we want to make a conservative prediction, aka increase likelihood that the model produces a negative error.
At the moment we are using LightGBM'…
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### Describe the feature you want to add to this project
Hi,
There are already good tutorials for time series forecasting, but they mainly focus on statistical model.
Is it possible to create one…
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The Sklearn API provides a simple way of specifying custom objective functions and evaluation metrics:
```
********* Sklearn API **********
# default lightgbm model with sklearn api
gbm = lightg…