Questions tagged [predictor-importance]

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Average of importance gain for a categorical variable

Suppose I have a set of M categorical variables, some of them with a different number of categories (for instance, var1 has five categories, var2 has three, etc). I train an XGBoost model on a numeric ...
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0answers
24 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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0answers
17 views

Find out which attribute of a movie causes the most variation in score

I'm tinkering around with a subset of the IMDb dataset, and have been thinking about what specific attributes of a movie impact its user rating. I am looking to survey what methods can be used to find ...
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0answers
8 views

What are good public datasets for time series analysis with “certified” (by papers in the literature) good predictors of the target variable?

I have to test different models for time series forecasting and predictors (exogenous covariates) goodness evaluation and I would like to use datasets used in relevant scientific publications that ...
2
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1answer
96 views

Feature Importance

I have a dataset with 10 features. I've computed the feature importance using permutation importance with cross-validation from eli5, after fitting an extremely randomized trees (ET) classifier form ...
1
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1answer
108 views

Feature importance after PCA (or other dimensionality reduction methods)

I have text data which I one hot encoded and then used PCA on it (although I'm experimenting with other methods as well, LDA, NMF..). I am using the result of the dimensionality reduction as an input ...
1
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1answer
129 views

Get insights from Random forest::Variable Importance analysis

I run variable importance on my Panel data (TV viewing over specific period) which consists of the old-Panel (Panel 0) and the new panel (Panel 1) I am interested in understanding the differences in ...
6
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1answer
95 views

Will unnecessary features harm the tree based model?

Is it necessary to drop noisy features (eg column of random numbers) from tree features? I think it's not. sometimes it may benefit but will never cause any harm to the model. Because at each split ...
2
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2answers
4k views

How to implement feature selection for categorical variables (especially with many categories)?

I've been trying to get some ideas of how I could treat categorical variables when doing feature selection. Mainly I've been running Random Forest feature importance on Python for which preprocessing ...
3
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1answer
313 views

Interpretation of variable or feature importance in Random Forest

I'm currently using Random Forest to train some models and interpret the obtained results. One of the features I want to analyze further, is variable importance. The thing is I am not familiar on how ...
3
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1answer
4k views

XGBoost: Quantifying Feature Importances

I need to quantify the importance of the features in my model. However, when I use XGBoost to do this, I get completely different results depending on whether I use the variable importance plot or the ...
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2answers
40 views

What to optimize for when asked to find the most important features

I have a binary classification problem, let's say people can buy or not buy a certain product. Now unlike a standard prediction task, I only want to find which features are the most important for the ...
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2answers
828 views

Is it possible to cluster data according to a target?

I was wondering if there exists techniques to cluster data according to a target. For example, suppose we want to find groups of customers likely to churn: Target is churn. We want to find clusters ...
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3answers
206 views

RF and DT overfitting

I am new with Machine Learning and I started with some lessons in Kaggle. There, I learnt how to use DecisionTreeRegressor() and ...