Questions tagged [xgbregressor]
42 questions
3
votes
1 answer
importance ranking: error must be an object of class xgb.Booster
I ran a xgboost regression forecast (also tried to complete it with the xgb.Booster.complete). When trying to get the xgb.importance, I get the error massage
Error in xgboost::xgb.importance(case_xgbm) : model: must be an
object of class…
user12938856
3
votes
1 answer
How to solve this question (Parameters: { "eval_set", "verbose" } might not be used.?
When I use the XGBoostRegressor to predict the Stock Price, and I try to fit the model.
# XGBoostRegressor
parameters = {
'n_estimators': [100, 200, 300, 400],
'learning_rate': [0.001, 0.005, 0.01, 0.05],
'max_depth': [8, 10, 12,…
Max
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2
votes
1 answer
how to properly initialize a child class of XGBRegressor?
I want to build a quantile regressor based on XGBRegressor, the scikit-learn wrapper class for XGBoost. I have the following two versions: the second version is simply trimmed from the first one, but it no longer works.
I am wondering why I need to…
Li-Pin Juan
- 1,156
- 1
- 13
- 22
1
vote
1 answer
Predict at a finer spatial scale using XGBoost regression
I want to make a prediction at a finer spatial scale using XGBoost regression. I created a model at a coarse spatial scale and now I want to apply the model parameters at a finer scale. The issue is that at the finer spatial scale the xgb.DMatrix…
Nikos
- 426
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- 10
1
vote
0 answers
XGBoost regression
I have a data set with events related to the customer behavior and the revenue the customers generated. I'd like to use XGBoost regression in Python to find which variables are more important in predicting the revenue. So from what I understand, I…
Nata
- 49
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1
vote
1 answer
Why does my machine learning model perform poorly with batch training?
My machine learning model (xgboost regressor) seems to perform worse when training in batches (i.e epochs > 1). If I change the number of epochs to 1 (i.e. no batches), my model score is near 93%. That's great However, when I set the number of…
John Doe
- 185
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1
vote
0 answers
R- Xgboost: Error in xgb.DMatrix unused argument
This is my first question here so I'm sorry if I'm not clear.
I was building an Xgboost model to forecast multiple time series. I've created the train and test xgb.DMatrix, also the xgb_trcontrol and xgb_grid tunning parameters, nevertheless when I…
Mateo Quiguirí
- 11
- 1
1
vote
0 answers
Feature importance without label for time-series data with large number of columns/features
I have a sample time-series dataset (23, 14291), which is a pivot table count for 24hrs count for some users; I'm trying to filter some of the columns/features which they don't have a time-series based nature and filter columns to reach meaningful…
Mario
- 1,631
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1
vote
1 answer
Why does my XBGoost model have a good accuracy for training and testing dataset, but poor one for predicting an held out dataset?
I'm currently working on a XGBoost regression model to predict ticket bookings.
My issue is that my model has a good accuracy for the training set (around 96%) and for the testing set (around 94%) but when I try to use the model to predict my…
Léa Joubert
- 11
- 1
1
vote
1 answer
Installing XGBoost on iMac M1 with GPU Support
I currently wrote some script for running XGBoost on my M1 iMac computer. I have installed XGBoost already within conda-forge as seen:
...
wheel 0.37.0 pyhd8ed1ab_1 conda-forge
xgboost 1.5.0 …
M. Fire
- 117
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- 6
0
votes
0 answers
Negative MAE value in XGBRegressor
Background: I have a tabular dataset and I am trying to predict price values. Two type of features are available where some columns are categorical variables(as dummy) and other features where the values vary between 0 and 1.
from xgboost import…
chrismoltisanti
- 39
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0
votes
1 answer
XGBRegressor： The results of GPU calculation and calculation without GPU are different
My code is here:
xgb = XGBRegressor(
max_depth= int(3.1847420232679196),
n_estimators = int(27.03977712011383),
subsample = 0.9130850193972424,
tree_method = 'gpu_hist',
gpu_id=0
)
xgb.fit(x_train,…
Ohhhhh
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0
votes
0 answers
XGBoost train_model function fails when adding a learning rate hyperparameter (using Snowpark)
I'm trying to add a learning rate hyperparameter to my train_model function, which uses XGBoost for regression in a Snowflake environment. However, whenever I include the learning rate parameter, the function fails with an error. The function works…
0
votes
0 answers
Timeseries forecasting training issue for XGBoost in Python
I'm doing multistep univariate timeseries forecasting with XGBRegressor and MultiOutputRegressor, i have sliced train data with varying inputs ex:[(x,y),(250,60),(329,50)...], is there any way I can train these inputs on MultiOutputRegressor without…
hitesh dsouza
- 21
- 1
0
votes
0 answers
Errors using customized loss function for quantile regression with XGBoost
I am trying out the customized loss function for quantile regression with XGBoost from https://gist.github.com/Nikolay-Lysenko/06769d701c1d9c9acb9a66f2f9d7a6c7 which is as follows:
import numpy as np
def xgb_quantile_eval(preds, dmatrix,…
Nata
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