Questions tagged [catboost]

CatBoost is an open-source gradient boosting on decision trees library with categorical features support out of the box for Python & R

Filter by
Sorted by
Tagged with
0 votes
0 answers
37 views

How symmetric trees reduce overfitting?

I was trying to think of how symmetric trees deal with the problem of overfitting. But, all I can think is that since a symmetric tree has more (or equal number of) leaves as compared to any other ...
0 votes
0 answers
18 views

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 $...
1 vote
0 answers
93 views

Why are my catboost predictions pushed towards 0 and 1 and how to smooth it? [closed]

I am using catboost in a classification problem with extreme unbalanced classes (positive class consists of ~ 0.25% of all observations). I fitted a model using catboost in R and got a very good ...
  • 11
1 vote
0 answers
32 views

Total number of learned weights/parameters in CatBoost model?

I wasn't really able to find this anywhere in the documentation, or after searching through the model object itself (though it must be there somewhere, of course. The ...
1 vote
1 answer
84 views

Generalization of model performance (AUC) and tuning of a catboost classifier

I was wondering if it is good practice to overfit on the training data while tuning a catboost classifier for a binary outcome. Wouldn't it be better to reguralize until validation error equals ...
2 votes
1 answer
265 views

How do Ordered Target Statistics work for CatBoost?

This question follows closely this paper . I'm trying to fully understand how Ordered Target Statistics (TS) (for CatBoost) works. E.g. the CatBoost algorithm uses this method to group categorical ...
  • 218
3 votes
1 answer
247 views

Any reasons to prefer neural networks over boosting methods in tabular data?

Based on Kaggle winners data, it seems that ensemble boosting methods like XGBOOST, LIGHTGBM, CATBOOST are the top choices when dealing with structured or tabular data for maximizing the prediction ...
  • 118
0 votes
0 answers
93 views

High precision and low recall but with a balanced dataset

When i evaluated my model (CatBoost classifier), I noticed that my model has high precision and low recall (Recall: 0.59, Precision: 0.89) but the classes are perfectly balanced (1: 45.5, 2: 54.5) and ...
1 vote
0 answers
44 views

Analytical expression of a CatBoost regression model in R

When adjusting a multiparametric regression model, an analytical expression that characterizes the fitted model (e.g., in a linear multiparametric regression, the equation is $\hat\beta= \hat\beta_o+\...
1 vote
1 answer
72 views

If evaluation set is the same as training set, why would the evaluation error be different from training error?

I understand the use of evaluation set for parameter tuning and over-fitting in general. The examples in the evaluation set should be unseen and different from training set. However, in the following ...
1 vote
0 answers
137 views

Role of weighted quantile sketch in XGBoost, LightGBM and CatBoost

Have i understood it correctly if i say that "weighted quantile sketch" allows XGBoost to use histogram search on feature values for split finding? Also, do LightGBM or CatBoost use ...
2 votes
0 answers
82 views

Looking for information regarding tree-based gradient boosting algorithms comparative performance on data sets with different underlying properties

I have a difficult time finding any theoretical or empirical comparative research regarding the tree-based gradient boosting algorithms on data sets with different underlying properties. Is there any ...
2 votes
1 answer
2k views

Why does LightGBM Classifier gives some folks a probability of 1 of belonging in a class with log-loss?

I'm trying to use the LightGBM package in python for a multi-class classification problem and I'm baffled by its results. For a minority of the population, LightGBM predicts a probability of 1 (...
2 votes
1 answer
2k views

catboost does not overfit - how is that possible?

I'm fitting and evaluating a CatBoostRegressor and a XGBRegressor to the same regression problem. I tried matching their ...
  • 2,738
2 votes
0 answers
270 views

Gradient boosting (GB) splitting methods (categorical features)

Regarding categorical features - ordinary trees treat categorical features in two main ways, CART - considers only binary splitting, those computing the mean response value (y_mean_i per each category ...
  • 21
2 votes
1 answer
4k views

L2 Regularization in CatBoost

I am studying the CatBoost paper https://arxiv.org/pdf/1706.09516.pdf (particularly Function BuildTree in page 16), and noticed that it did not mention regularization. In particular, split selection ...
1 vote
1 answer
1k views

negative value of prediction from a training set that only contains positives

a catboost model recently gave me a % of predictions that are negative while none of the training set contains negative values for the label. How is this possible especially in cases where the % of ...
1 vote
1 answer
566 views

Model Size of Random Forest VS CatBoost

I trained models based on the same dataset, using random forest (sklearn) and CatBoost. I use n_estimators=1000 for random forest, and n_estimators(iterations)=1000 for CatBoost. The random forest ...
0 votes
0 answers
22 views

Tweak Model or Process to Focus More on Category Values for Regression

I have built a machine learning model using Catboost and I noticed something as I examine the results. When I am looking at the results there is a big fluctuation in the errors between my test set and ...
  • 11
3 votes
1 answer
786 views

Negative Feature Importance Value in CatBoost LossFunctionChange

I am using CatBoost for ranking task. I am using QueryRMSE as my loss function. I notice for some features, the feature importance values are negative and I don't know how to interpret them. It says ...
1 vote
2 answers
583 views

AUPRC vs AUROC and updating training set in quasi-classification problem

I have an unbalanced classification problem (95% "0", 5% "1") regarding quality control."0" means "no problem" and "1" means "problem". I'm not predicting real cases one by one, this is, my client ...
3 votes
1 answer
1k views

Feature Interaction Strength in Catboost

I was wondering if anyone knew how the feature interaction strength is calculated in the catboost package. The documentation https://catboost.ai/docs/concepts/output-data_feature-analysis_feature-...
3 votes
1 answer
2k views

(Low cardinality) categorical features handling in gradient boosting libraries

In some popular gradient boosting libraries (lgb, catboost), they all seems like can handle categorical inputs by just specifying the column names of the categorical features, and pass it into a ...
  • 377
0 votes
1 answer
513 views

Catboost Regression. Function Extrapolation

I'm new at ML and have a problem with catboost. So, I want to predict function value (For example cos | sin etc.). I went over everything but my prediction is always straight line Is it possible and ...
1 vote
1 answer
93 views

catboost ignoring my holiday category

I'm experimenting with catboost, predicting electricity demand from temperature, timeofday, dayofweek and if a day is a public holiday or not (and a few other continuous and categorical columns but ...
4 votes
1 answer
211 views

Please correct my assumption on how regression trees work

I'm trying to understand how regression trees work, I've been experimenting with catboost and xgboost in python, and I'm getting results which I don't expect, can someone please clarify (and apologies ...
-1 votes
1 answer
2k views

What are the key hyperparameters to tune in CatBoost?

I've used XGBoost for a long time but I'm new to CatBoost. If I wanted to run a sklearn RandomizedSearchCV, what are CatBoost's hyperparameters worthwhile including for a binary classification problem?...
  • 425
4 votes
1 answer
1k views

IncToDec Catboost Explained

I am struggling to understand how the overfitting detector with catboost works: https://tech.yandex.com/catboost/doc/dg/concepts/overfitting-detector-docpage/#overfitting-detector I am finding ...
  • 7,790