Model description
This is a regression model on MPG dataset trained for this kaggle tutorial.
Intended uses & limitations
This model is not ready to be used in production.
Training Procedure
Hyperparameters
The model is trained with below hyperparameters.
Click to expand
| Hyperparameter | Value |
|---|---|
| ccp_alpha | 0.0 |
| criterion | squared_error |
| max_depth | |
| max_features | |
| max_leaf_nodes | |
| min_impurity_decrease | 0.0 |
| min_samples_leaf | 1 |
| min_samples_split | 2 |
| min_weight_fraction_leaf | 0.0 |
| random_state | |
| splitter | best |
Model Plot
The model plot is below.
DecisionTreeRegressor()Please rerun this cell to show the HTML repr or trust the notebook.
DecisionTreeRegressor
DecisionTreeRegressor()
## Evaluation Results
You can find the details about evaluation process and the evaluation results.
| Metric | Value |
|---|---|
| Mean Squared Error | 10.86399394359616 |
| R-Squared | <function r2_score at 0x7f743fc54b00> |
How to Get Started with the Model
Use the code below to get started with the model.
from skops.io import load
import json
import pandas as pd
clf = load("pipeline.skops")
with open("config.json") as f:
config = json.load(f)
clf.predict(pd.DataFrame.from_dict(config["sklearn"]["example_input"]))
Model Card Authors
This model card is written by following authors:
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Model Card Contact
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Citation
Below you can find information related to citation.
BibTeX:
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