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Showing posts with the label Xgboost

Xgboost With Gridsearchcv, Scaling, Pca, And Early-stopping In Sklearn Pipeline

I want to combine a XGBoost model with input scaling and feature space reduction by PCA. In additio… Read more Xgboost With Gridsearchcv, Scaling, Pca, And Early-stopping In Sklearn Pipeline

How Can I Know Which Is The Positive Class Value And Negative Class Value For Xgboost?

I am working with an imbalanced dataset where I have a class variable of 2 different values: 0 and … Read more How Can I Know Which Is The Positive Class Value And Negative Class Value For Xgboost?

Xgboost : The Least Populated Class In Y Has Only 1 Members, Which Is Too Few

Im using Xgboost implementation on sklearn for a kaggle's competition. However, im getting this… Read more Xgboost : The Least Populated Class In Y Has Only 1 Members, Which Is Too Few

Visualize Strengths And Weaknesses Of A Sample From Pre-trained Model

Let's say I'm trying to predict an apartment price. So, I have a lot of labeled data, where… Read more Visualize Strengths And Weaknesses Of A Sample From Pre-trained Model

Xgboost Predictor In R Predicts The Same Value For All Rows

I looked into the the post on the same thing in Python, but I want a solution in R. I'm working… Read more Xgboost Predictor In R Predicts The Same Value For All Rows

Why Xgboost.cv And Sklearn.cross_val_score Give Different Results?

I'm trying to make a classifier on a data set. I first used XGBoost: import xgboost as xgb impo… Read more Why Xgboost.cv And Sklearn.cross_val_score Give Different Results?