Questions tagged [catboost]

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How to handle tags/lists with CatBoost?

I have database like this: Id, type, category1, category2, tags 1, ‘cosmetics’, 123, 456, [446, 354] 2, ‘electronics’, 234, 213, [55, 978, 12] … And I want to predict some value with ...
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How does Catboost regressor deal with categorical features at predict time?

I understand that Catboost regressor uses target-based encoding to convert categorical features to numerical features when training. But how does Catboost deal with categorical features at predict ...
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Problem with Duplicate Data in Case of CatBoost

We know that while converting categorical variables to numerics, CatBoost uses the following formula (source: documentation): Now, suppose there are 2 duplicate data entries. Ideally, the value of ...
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Using class weights with training on imbalanced dataset gives worse result w.r.t logloss than without weights

I am trying to make a model for usual binary classification that is able to predict probabilities of classes. I have not very big dataset of 10k objects where classes are imbalanced as 80:20 and tried ...
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Catboost not working properly when I remove non important variables (source of randomness?)

I was wondering if anyone has encountered the same. The thing is, when I run a catboost boosting model, delete non important variables (feature importance by prediction importance = 0, in fact these ...
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Analysis of prediction shift problem in gradient boosting

I was going through the Catboost paper section 4.1 where they talk about the 'Analysis of prediction shift' using an example consisting of 2 features which are bernoulli random variables. I am unable ...
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How to tell CatBoost which feature is categorical?

I am excited to learn that CatBoost can handle categorical features by itself. One of my features, Department ID, is categorical. However, it looks like numeric, since the values are like 1001, 1002, ....
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How to tune a Catboost Regressor

I have been trying to study about hyperparameter tuning for CatBoost regressor for my regression problem. The only issue being I can't figure out what all parameters should I tune for my use case out ...
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Confused about CatRegressor feature importance vs SHAP

I'm confused about result from a CatBoostRegressor-model. I follow this article: https://towardsdatascience.com/catboost-regression-in-6-minutes-3487f3e5b329 My confusion is about the difference in ...
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Are linear models better when dealing with too many features? If so, why?

I had to build a classification model in order to predict which what would be the user rating by using his/her review. (I was dealing with this dataset: Trip Advisor Hotel Reviews) After some ...
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Why feature engineering and filling NaN's reduce score?

I used CatBoost for InClass Kaggle competition. I have tried various strategies to filling NaN values. Convert float binary variables to categorical. Add new categorical features (from age, for ...
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Catboost not able to handle a very simple dataset?

This is a post from a newbie and so might be a really poor question based on lack of knowledge. Thank you kindly! I'm using Catboost, which seems excellent, to fit a trivial dataset. The results are ...
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Difference between model score on test part and Kaggle public score

I tested my CatBoostModel model on part of data and get 0.92 score, but Kaggle public score was 0.9. I found new hyperparameters via randomsearch, new model score was 0.925, but on Kaggle score fell ...
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How to use the eval set in catboost appropriately?

Let's say you have a dataset, and you split it into 80% training and 20% testing. Naturally, you want to find the optimal hyperparameters for your model, so with the training set, you plan to do cross ...
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303 views

Unable to tune hyperparameters for CatBoostRegressor

I am trying to fit a CatBoostRegressor to my model. When I perform K fold CV for the baseline model everything works fine. But when I use Optuna for hyperparameter tuning, it does something really ...
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How do Classification Algorithms such as Catboost and Random Forest parse test data?

I would like to know how classification works with the algorithms listed above. My specific question is this, say I have a high signal continuous feature which has a certain distribution and I train a ...
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Model Dump Parser (like XGBFI) for LightGBM and CatBoost

Currently my employer has multiple GLM in a live environment. I am interested in identifying new features and interactions to enhance the accuracy of these GLM; for now I am limited to the GLM ...
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Why does Catboost outperform other boosting algorithms?

I have noticed while working with multiple datasets that catboost with its default parameters tends to outperform lightgbm or xgboost with its default parameters even on a tabular dataset with no ...
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Does Gradient Boosting perform n-ary splits where n > 2?

I wonder whether algorithms such as GBM, XGBoost, CatBoost, and LightGBM perform more than two splits at a node in the decision trees? Can a node be split into 3 or more branches instead of merely ...
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Feature Selection before modeling with Boosting Trees

I have read in some papers that the subset of features chosen for a boosting tree algorithm will make a big difference on the performanceso I've been trying RFE, Boruta, Clustering variables, ...
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Catboost multiclassification evaluation metric: Kappa & WKappa

I am working on an unbalanced classification problem and i want to use Kappa as my evaluation metric. Considering the classifier accepts weights (which i have given it), should i still be using ...
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training gradient boosting algorithm in python testing in Golang

What are the best strategy to train and save a gradient boosting algorithm, e.g. LightGBM or XGboost or Catboost in Python but load the model in GoLang and make prediction with Golang ?
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How to understand the definition of Greedy Target-based Statistics in the CatBoost paper

There is a method named Target statistics to deal with categorical features in the catboost paper. I still some confusion about the mathematical form. Could you some guys to expain how to compute it! $...
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What is the concept behind the categorical-encoding used in the CatBoost benchmark problems?

I'm working through CatBoost quality benchmark problems (here). I'm particularly intrigued by the methodology adopted to convert categorical features to numerical values as described in the ...
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1 vote
2 answers
397 views

Does gradient boosting algorithm error always decrease faster and lower on training data?

I am building another XGBoost model and I'm really trying not to overfit the data. I split my data into train and test set and fit the model with early stopping based on the test-set error which ...
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5 votes
1 answer
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How to achieve SHAP values for a CatBoost model in R?

I'm asked to create a SHAP analysis in R but I cannot find it how to obtain it for a CatBoost model. I can get the SHAP values of an XGBoost model with ...
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21 votes
1 answer
10k views

Lightgbm vs xgboost vs catboost

I've seen that in Kaggle competitions people are using lightgbms where they used to use xgboost. My question is: when would you rather use xgboost instead of lightgbm? What about catboost?
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