metadata

library_name: sklearn
tags:
  - sklearn
  - skops
  - tabular-regression
model_file: pipeline.skops
widget:
  structuredData:
    acceleration:
      - 20.7
      - 17
      - 18.6
    cylinders:
      - 4
      - 4
      - 4
    displacement:
      - 98
      - 120
      - 120
    horsepower:
      - '65'
      - '88'
      - '79'
    model year:
      - 81
      - 75
      - 82
    origin:
      - 1
      - 2
      - 1
    weight:
      - 2380
      - 2957
      - 2625

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.

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:

[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:

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