metadata
library_name: sklearn
tags:
- sklearn
- skops
- tabular-regression
widget:
structuredData:
AveBedrms:
- 0.9806451612903225
- 1.0379746835443038
- 0.9601449275362319
AveOccup:
- 2.587096774193548
- 2.8658227848101268
- 2.6449275362318843
AveRooms:
- 7.275268817204301
- 5.39493670886076
- 6.536231884057971
HouseAge:
- 38
- 25
- 39
Latitude:
- 37.44
- 37.31
- 34.16
Longitude:
- -122.19
- -122.03
- -118.07
MedInc:
- 9.3198
- 5.3508
- 6.4761
Population:
- 1203
- 1132
- 730
Model description
[More Information Needed]
Intended uses & limitations
[More Information Needed]
Training Procedure
Hyperparameters
The model is trained with below 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 |
n_estimators | 100 |
n_jobs | |
oob_score | False |
random_state | |
verbose | 0 |
warm_start | False |
Model Plot
The model plot is below.
RandomForestRegressor()In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
RandomForestRegressor()
Evaluation Results
You can find the details about evaluation process and the evaluation results.
Metric | Value |
---|
How to Get Started with the Model
Use the code below to get started with the model.
Click to expand
[More Information Needed]
Model Card Authors
This model card is written by following authors:
[More Information Needed]
Model Card Contact
You can contact the model card authors through following channels: [More Information Needed]
Citation
Below you can find information related to citation.
BibTeX:
[More Information Needed]