Edit model card
YAML Metadata Error: "widget" must be an array

Model description

This is a passive-agressive regression model used for continuous training. Find the notebook here

Intended uses & limitations

This model is not ready to be used in production. It's trained to predict MPG a car spends based on it's attributes.

Training Procedure

Hyperparameters

The model is trained with below hyperparameters.

Click to expand
Hyperparameter Value
C 0.01
average False
early_stopping False
epsilon 0.1
fit_intercept True
loss epsilon_insensitive
max_iter 1000
n_iter_no_change 5
random_state
shuffle True
tol 0.001
validation_fraction 0.1
verbose 0
warm_start False

Model Plot

The model plot is below.

PassiveAggressiveRegressor(C=0.01)
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

How to Get Started with the Model

Use the code below to get started with the model.

import joblib
import json
import pandas as pd
clf = joblib.load(skops47mqlzp0)
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:

[More Information Needed]
Downloads last month
0
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.