I am trying to use XGBoost for classification. I am pretty doubtful on its accuracy. I have applied it with default parameters and the precision is 100%. xg_c
I use xgboost to do a multi-class classification of spectrogram images(data link: automotive target classification). The class number is 5, training data includ
I was running this code on RStudio param <- list(colsample_bytree = 1, subsample = .6, booster = "gbtree", max_dept
It gives a regression prediction as continuous score with negative values, like -1.27544 < x < 6.68112. How I interpret the negatives?
I am using a scikit-learn pipeline with XGBRegressor. Pipeline is working good without any error. When I am prediction with this pipeline, I am predicting the
I pulled some ML code that ran on kaggle (linux) and tried to run it in a jupyter notebook on a windows machine. Here is the code (some of it): ##### RUN XGBOO
My first multiclass classication. I have values X and Y. Y have 5 values [0,1,2,3,4]. But i get this "multiclass format is not supported". Understand that i nee
Using xgboost.Booster.predict can only get the prediction result of all the tree or the predicted leaf of each tree. But how could I get the prediction value of
I implemented a univariate xgboost time series using the following code, def series_to_supervised(data, n_in=1, n_out=1, dropnan=True): n_vars = 1 if type(d
I use xgboost to train a classification model. GridCVSearch gives the best max_depth=1. This means all my hundreds of trees are split at a single node. Does t
I ran this code on cmd and I face this error. _pickle.UnpicklingError: NEWOBJ class argument isn't a type object my app.py goes like this: # -*- coding: utf-8 -
I've spent a good deal of time trying to find out what these "subsample", "colsample_by_tree", and "colsample_bylevel" actually did in XGBClassifier() but I can
When I run a Tweedie GLM, one can get the prediction from the link by doing exp(link). To get the prediction for a Tweedie GLM, I get the prediction from the li