davidgamma/mltwstock

Model description

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Intended uses & limitations

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Training Procedure

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Hyperparameters

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Hyperparameter	Value
objective	reg:squarederror
base_score
booster
callbacks
colsample_bylevel
colsample_bynode
colsample_bytree
device
early_stopping_rounds
enable_categorical	False
eval_metric
feature_types
gamma
grow_policy
importance_type
interaction_constraints
learning_rate	0.01
max_bin
max_cat_threshold
max_cat_to_onehot
max_delta_step
max_depth
max_leaves
min_child_weight
missing	nan
monotone_constraints
multi_strategy
n_estimators
n_jobs
num_parallel_tree
random_state
reg_alpha
reg_lambda
sampling_method
scale_pos_weight
subsample
tree_method
validate_parameters
verbosity

Model Plot

XGBRegressor(base_score=None, booster=None, callbacks=None,colsample_bylevel=None, colsample_bynode=None,colsample_bytree=None, device=None, early_stopping_rounds=None,enable_categorical=False, eval_metric=None, feature_types=None,gamma=None, grow_policy=None, importance_type=None,interaction_constraints=None, learning_rate=0.01, max_bin=None,max_cat_threshold=None, max_cat_to_onehot=None,max_delta_step=None, max_depth=None, max_leaves=None,min_child_weight=None, missing=nan, monotone_constraints=None,multi_strategy=None, n_estimators=None, n_jobs=None,num_parallel_tree=None, random_state=None, ...)

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Evaluation Results

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How to Get Started with the Model

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Model Card Authors

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Citation

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