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xgboost-example

merve / xgboost-example

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Model's Last Updated: January 20 2023
tabular-regression

Introduction of xgboost-example

Model Details of xgboost-example

Model description

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Intended uses & limitations

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Training Procedure
Hyperparameters

The model is trained with below hyperparameters.

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Hyperparameter Value
memory
steps [('onehotencoder', OneHotEncoder(handle_unknown='ignore', sparse=False)), ('xgbregressor', XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,
colsample_bynode=1, colsample_bytree=1, enable_categorical=False,
gamma=0, gpu_id=-1, importance_type=None,
interaction_constraints='', learning_rate=0.300000012,
max_delta_step=0, max_depth=5, min_child_weight=1, missing=nan,
monotone_constraints='()', n_estimators=100, n_jobs=8,
num_parallel_tree=1, predictor='auto', random_state=0, reg_alpha=0,
reg_lambda=1, scale_pos_weight=1, subsample=1, tree_method='exact',
validate_parameters=1, verbosity=None))]
verbose False
onehotencoder OneHotEncoder(handle_unknown='ignore', sparse=False)
xgbregressor XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,
colsample_bynode=1, colsample_bytree=1, enable_categorical=False,
gamma=0, gpu_id=-1, importance_type=None,
interaction_constraints='', learning_rate=0.300000012,
max_delta_step=0, max_depth=5, min_child_weight=1, missing=nan,
monotone_constraints='()', n_estimators=100, n_jobs=8,
num_parallel_tree=1, predictor='auto', random_state=0, reg_alpha=0,
reg_lambda=1, scale_pos_weight=1, subsample=1, tree_method='exact',
validate_parameters=1, verbosity=None)
onehotencoder__categories auto
onehotencoder__drop
onehotencoder__dtype <class 'numpy.float64'>
onehotencoder__handle_unknown ignore
onehotencoder__max_categories
onehotencoder__min_frequency
onehotencoder__sparse False
xgbregressor__objective reg:squarederror
xgbregressor__base_score 0.5
xgbregressor__booster gbtree
xgbregressor__colsample_bylevel 1
xgbregressor__colsample_bynode 1
xgbregressor__colsample_bytree 1
xgbregressor__enable_categorical False
xgbregressor__gamma 0
xgbregressor__gpu_id -1
xgbregressor__importance_type
xgbregressor__interaction_constraints
xgbregressor__learning_rate 0.300000012
xgbregressor__max_delta_step 0
xgbregressor__max_depth 5
xgbregressor__min_child_weight 1
xgbregressor__missing nan
xgbregressor__monotone_constraints ()
xgbregressor__n_estimators 100
xgbregressor__n_jobs 8
xgbregressor__num_parallel_tree 1
xgbregressor__predictor auto
xgbregressor__random_state 0
xgbregressor__reg_alpha 0
xgbregressor__reg_lambda 1
xgbregressor__scale_pos_weight 1
xgbregressor__subsample 1
xgbregressor__tree_method exact
xgbregressor__validate_parameters 1
xgbregressor__verbosity
Model Plot

The model plot is below. 

Pipeline(steps=[('onehotencoder',OneHotEncoder(handle_unknown='ignore', sparse=False)),('xgbregressor',XGBRegressor(base_score=0.5, booster='gbtree',colsample_bylevel=1, colsample_bynode=1,colsample_bytree=1, enable_categorical=False,gamma=0, gpu_id=-1, importance_type=None,interaction_constraints='',learning_rate=0.300000012, max_delta_step=0,max_depth=5, min_child_weight=1, missing=nan,monotone_constraints='()', n_estimators=100,n_jobs=8, num_parallel_tree=1, predictor='auto',random_state=0, reg_alpha=0, reg_lambda=1,scale_pos_weight=1, subsample=1,tree_method='exact', validate_parameters=1,verbosity=None))])
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
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Pipeline(steps=[('onehotencoder',OneHotEncoder(handle_unknown='ignore', sparse=False)),('xgbregressor',XGBRegressor(base_score=0.5, booster='gbtree',colsample_bylevel=1, colsample_bynode=1,colsample_bytree=1, enable_categorical=False,gamma=0, gpu_id=-1, importance_type=None,interaction_constraints='',learning_rate=0.300000012, max_delta_step=0,max_depth=5, min_child_weight=1, missing=nan,monotone_constraints='()', n_estimators=100,n_jobs=8, num_parallel_tree=1, predictor='auto',random_state=0, reg_alpha=0, reg_lambda=1,scale_pos_weight=1, subsample=1,tree_method='exact', validate_parameters=1,verbosity=None))])
OneHotEncoder(handle_unknown='ignore', sparse=False)
XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,colsample_bynode=1, colsample_bytree=1, enable_categorical=False,gamma=0, gpu_id=-1, importance_type=None,interaction_constraints='', learning_rate=0.300000012,max_delta_step=0, max_depth=5, min_child_weight=1, missing=nan,monotone_constraints='()', n_estimators=100, n_jobs=8,num_parallel_tree=1, predictor='auto', random_state=0, reg_alpha=0,reg_lambda=1, scale_pos_weight=1, subsample=1, tree_method='exact',validate_parameters=1, verbosity=None)
Evaluation Results

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How to Get Started with the Model

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Model Card Authors

This model card is written by following authors:

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Model Card Contact

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Citation

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BibTeX: 

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More Information About xgboost-example huggingface.co Model

xgboost-example huggingface.co

xgboost-example huggingface.co is an AI model on huggingface.co that provides xgboost-example's model effect (), which can be used instantly with this merve xgboost-example model. huggingface.co supports a free trial of the xgboost-example model, and also provides paid use of the xgboost-example. Support call xgboost-example model through api, including Node.js, Python, http.

xgboost-example huggingface.co Url

https://huggingface.co/merve/xgboost-example

merve xgboost-example online free

xgboost-example huggingface.co is an online trial and call api platform, which integrates xgboost-example's modeling effects, including api services, and provides a free online trial of xgboost-example, you can try xgboost-example online for free by clicking the link below.

merve xgboost-example online free url in huggingface.co:

https://huggingface.co/merve/xgboost-example

xgboost-example install

xgboost-example is an open source model from GitHub that offers a free installation service, and any user can find xgboost-example on GitHub to install. At the same time, huggingface.co provides the effect of xgboost-example install, users can directly use xgboost-example installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

xgboost-example install url in huggingface.co:

https://huggingface.co/merve/xgboost-example

Url of xgboost-example

xgboost-example huggingface.co Url

Provider of xgboost-example huggingface.co

merve
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