I've trained dataset using XGB Classifier, but I got this error in local. It worked on Colab and also my friends don't have any problem with same code. I don't know what that error means... Invalid...

I have a dataset like so: print(X_test.dtypes) metric1 int64 rank float64 device_type int8 NA_estimate float64 When I try to make predictions on this data set, I get the following error: y_test_pr...

Context I am trying to use a custom loss function for an XGBoost binary classifier. The idea was to implement in XGBoost the soft-Fbeta loss, which I read about here. Simply put: instead of using t...

I am using a XGBClassifier and try to do a grid search in order to tune some parameters, and I get this warning : WARNING: ../src/learner.cc:1517: Empty dataset at worker: 0 whenever I launch the c...

What is difference between xgboost.plot_importance() and model.feature_importances_ in XGBclassifier. so here I make some dummy data import numpy as np import pandas as pd # generate some random da...

I am dealing with a classification problem with 3 classes [0,1,2], and imbalanced class distribution as shown below. I want to apply XGBClassifier (in Python) to this classification problem, but t...

The SHAP values returned from tree explainer's .shap_values(some_data) gives different dimensions/results for XGB as for random forest. I've tried looking into it, but can't seem to find why or how...

I've the following code eval_set = [(X_train, y_train), (X_test, y_test)] eval_metric = ["auc","error"] In the following part, I'm training the XGBClassifier model model = XGBClassifier() %tim...

I am confused now about the loss functions used in XGBoost. Here is how I feel confused: we have objective, which is the loss function needs to be minimized; eval_metric: the metric used to repre...