Questions tagged [lightgbm]

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Math Behind GOSS (Gradient-Based One Side Sampling)?

As per my understanding through books & Google Search, GOSS (Gradient-Based One Side Sampling) is a novel sampling method that downsamples the instances on the basis of gradients. As we know ...
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1answer
48 views

What is Pruning & Truncation in Decision Trees?

Pruning & Truncation As per my understanding Truncation: Stop the tree while it is still growing so that it may not end up with leaves containing very low data points. One way to do this is to ...
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1answer
55 views

Random Forest VS LightGBM

Random Forest VS LightGBM Can somebody explain in-detailed differences between Random Forest and LightGBM? And how the algorithms work under the hood? As per my understanding from the documentation: ...
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18 views

Should the LightGBM score match the regularization?

If I set the parameter objective to regression_l1 and set the metric to mean absolute error in ...
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2answers
93 views

GridSearchCV for lightbgm classifier for multiclass problem

I am doing the following: ...
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0answers
47 views

Read back a saved LGBMClassifier model

I trained a LGBMClassifier model and saved in a file in this way: ...
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1answer
73 views

LightGBM vs Sklearn LightGBM- Mistake in Implementation- Exact same parameters giving different results

While passing the exact same parameters to LightGBM and sklearn's implementation of LightGBM, I am getting different results. Initially, I was getting the exact same results on doing this, however, I ...
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27 views

SHAP value analysis gives different feature importance on train and test set

Should SHAP value analysis be done on train or test set? What does it mean if the feature importance based on mean |SHAP value| is different between the train and test set of my lightgbm model? I ...
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27 views

if I got feature importance of xgboost/LightGBM what is next?

If I have feature importances of different variables in a xgboost/LightGBM model, how do I use this information? Is it better to just use the top n features and retrain the model? Does the feature ...
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0answers
80 views

Use LightGBM or FFM - imbalanced dataset

I have a highly imabalanced dataset but one that is not sparse. In train there are 1328 positives out of 104000. In validation ...
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1answer
18 views

LightGBM choice of evaluation metric

I have past data of a large number of people who applied for a loan and their movement through 8 different stages, from start of application to loan being paid out. I am trying to build a model that ...
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1answer
38 views

Sliding window approach using SVR & LightGBM

I'm working on a multivariate time series forecast using a couple of ML algorithms (Neural Networks, Support Vector Machines & Gradient boosting algorithms). I need to measure the performance of ...
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1answer
71 views

How to choose the model parameters (RandomizedSearchCV, .GridSearchCV) or manually

Faced with the task of selecting parameters for the lightgbm model, the question accordingly arises, what is the best way to select them? I used the RandomizedSearchCV method, within 10 hours the ...
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40 views

Comparing feature importance in LightGBM + Scikit

I have a model trained using LightGBM (LGBMRegressor), in Python, with scikit-learn. On a weekly basis the model in re-trained, and an updated set of chosen features and associated ...
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2answers
686 views

L1 & L2 Regularization in Light GBM

This question pertains to L1 & L2 regularization parameters in Light GBM. As per official documentation: reg_alpha (float, optional (default=0.)) – L1 ...
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1answer
240 views

Light GBM Regressor, L1 & L2 Regularization and Feature Importances

I want to know how L1 & L2 regularization works in Light GBM and how to interpret the feature importances. Scenario is: I used LGBM Regressor with RandomizedSearchCV (cv=3, iterations=50) on a ...
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1answer
84 views

Hyperparameter Tuning Time Series in Production

I have a time series data that handled using GDBT to predict the next value. I always use previous 30 days data to train daily, but overtime the data to predict and train is increased because the ...
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80 views

How to save a lightGBM model that updates predictions after each fold?

Hi When I use gradient boosting on Kaggle and large data sets, I run a code like this: ...
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1answer
16 views

Syntax of the inputs for LightGBM binary build (without python API)

I built the LightGBM binaries from https://github.com/microsoft/LightGBM. The build was successful, but the python API did not work for me. I am using the light gbm binary directly to run for time ...
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0answers
577 views

Differences between class_weight and scale_pos weight in LightGBM

I have a very imbalanced dataset with the ratio of the positive samples to the negative samples being 1:496. The scoring metric is the f1 score and my desired model is LightGBM. I am using the sklearn ...
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2answers
2k views

How to make LightGBM to suppress output?

I'm trying for a while to figure out how to "shut up" LightGBM. Especially, I want to suppress the output of LightGBM during training (the feedback on the boosting steps). My model is: ...
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0answers
129 views

How does L1 Loss work in lightGBM

From the paper, lightGBM does a subsampling according to sorted $|g_i|$, where $g_i$ is the gradient (for the loss function) at a data instance. My question is that, when the objective is L1 loss/...