Questions tagged [lightgbm]
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25
questions
3
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1answer
39 views
How the algorithms such as Xgboost and LightGBM fills the NAN (missing data)?
How the algorithms such as Xgboost and LightGBM fills the NAN ?
I know that they learn how to fill it but how they do it is my question and what is they method of learning how to fill the NAN?
2
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0answers
16 views
Correct interpretation of summary_plot shap graph
While through the various resources online to understand the shap plots, I ended up slightly confused. Find below my interpretation of the overall plot given in examples -
Shap value 0 for a feature ...
2
votes
1answer
45 views
Extremely high gain with LightGBM
I am working on a binary classification problem. The target variable is not linearly separable, so I've decided to use LightGBM with default parameters (I only play with n_estimators on range from 10 -...
0
votes
0answers
35 views
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 ...
6
votes
1answer
77 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 ...
1
vote
1answer
186 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:
...
0
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0answers
22 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 ...
-1
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2answers
192 views
1
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0answers
57 views
Read back a saved LGBMClassifier model
I trained a LGBMClassifier model and saved in a file in this way:
...
1
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1answer
177 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 ...
1
vote
0answers
42 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 ...
0
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0answers
28 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 ...
1
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0answers
111 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 ...
1
vote
1answer
24 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 ...
0
votes
1answer
51 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 ...
0
votes
1answer
127 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 ...
2
votes
0answers
59 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 ...
4
votes
2answers
1k 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 ...
1
vote
1answer
336 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 ...
0
votes
1answer
124 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 ...
1
vote
0answers
133 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:
...
0
votes
1answer
18 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 ...
2
votes
0answers
817 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 ...
0
votes
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:
...
1
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0answers
136 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/...
