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pppereira3/
hw4_mnar25_regressor_iter

Name: hw4_mnar25_regressor_iter
Availability: InStock

sklearn

skops

tabular-regression

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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
bootstrap	True
ccp_alpha	0.0
criterion	squared_error
max_depth
max_features	1.0
max_leaf_nodes
max_samples
min_impurity_decrease	0.0
min_samples_leaf	1
min_samples_split	2
min_weight_fraction_leaf	0.0
monotonic_cst
n_estimators	100
n_jobs
oob_score	False
random_state	42
verbose	0
warm_start	False

Model Plot

RandomForestRegressor(random_state=42)

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Evaluation Results

Metric	Value
rmse	0.235434

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Citation

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eval_method

The model is evaluated using test split, on rmse.

pppereira3/hw4_mnar25_regressor_iter

Model description

Intended uses & limitations

Training Procedure

Hyperparameters

Model Plot

Evaluation Results

How to Get Started with the Model

Model Card Authors

Model Card Contact

Citation

eval_method

pppereira3/
hw4_mnar25_regressor_iter