Questions tagged [predictor-importance]

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Using feature importance to decet latent variables and grouping

Is it possible to use feature importance from Random Forests (e.g. based on gini impurity) or other models to determine which features I can use to group the rows of my dataset homogeneously? For ...
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20 views

Aggregate SHAP importances from different models (algorithms)

A couple of questions on the SHAP approach to the estimation of feature importance. I would like to use the random forest, logistic regression, SVM, and kNN to train four classification models on a ...
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1answer
56 views

Positive or negative impact of features in prediction with Random Forest

In classification, when we want to get the importance of each variable in the random forest algorithm we usually use Mean Decrease in Gini or Mean Decrease in Accuracy metrics. Now is there a metric ...
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0answers
26 views

Why not use constant instead of permutation for model agnostic predictor importance?

I want to determine predictor importance. Ideal is to re-train same model on same dataset missing each variable in turn. This is too time consuming. The recommendation I have seen everywhere is to "...
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0answers
50 views

Keras most important features for text classification

I am working on a problem where I need to classify phrases in one of the two categories (let's A & B). I used the Keras SepCNN model (similar to this) for that and it is giving me some results. ...
5
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1answer
28 views

Identifying and Accounting for trend/seasonality in Predictor Variables

I'm currently working with a dataset that has been collected over several years, and I suspect my predictor variables are changing over time for their predictive power. I could go back year by year ...
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0answers
13 views

Model ensemble - using model associated with median (instead of mean) for calculation purposes (Explainability)

I have seen many model ensemble litterature. Most, if not all of it, consider averaging models. I was considering using the median instead of the mean. In general I would consider this a good ...
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0answers
30 views

Model-independent measures for feature importance given highly correlated features

I am currently working on a research project where the central question is which features drive the prediction of different models. The main issue is, that there is high (multi-)collinearity among ...
1
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1answer
34 views

How to check for “statistical significance” of categorical feature in black box models

Let's say we have a categorical feature $X_i$ and we have build a black-box classification model like xgboost with $X_i$ as one of many predictors. We'd like to ask a question: does $X_i$ affects the ...
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1answer
390 views

XGBoost Feature Importance, Permutation Importance, and Model Evaluation Criteria

I have built an XGBoost classification model in Python on an imbalanced dataset (~1 million positive values and ~12 million negative values), where the features are binary user interaction with web ...
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1answer
88 views

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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2answers
250 views

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

Should SHAP value analysis be done on the 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? ...
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21 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
12 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
163 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 ...
2
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0answers
58 views

different outcome of feature importance and coefficient from same data

I built a regression model to predict profit based on client, sales person, product category, client industry and client region. After trying several models with tuning hyperparameters, I found that ...
1
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1answer
280 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 ...
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1answer
232 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 ...
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1answer
99 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 ...
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2answers
6k 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
399 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
5k 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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3answers
1k 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
256 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 ...