Automate the Creation of Generalized Additive Models (GAMs)
Project description
autogam
Automate the Creation of Generalized Additive Models (GAMs)
Installation
$ pip install autogam
Usage
Example 1: Fitting AutoGAM on a Random Dataset
import numpy as np
import pandas as pd
from autogam.autogam import AutoGAM
# Generate a random dataset
df_random = pd.DataFrame({
'x1': np.random.uniform(0, 10, 100),
'x2': np.random.uniform(0, 10, 100),
'y': np.random.uniform(0, 10, 100)
})
# Fit the model using AutoGAM
ag_random = AutoGAM(df_random, 'y')
# Display the model summary
ag_random.summary()
# Display the performance metrics
ag_random.print()
Example 2: Fitting AutoGAM on the df_autos
Dataset
import pandas as pd
from statsmodels.gam.tests.test_penalized import df_autos
from autogam.autogam import AutoGAM
# Use the `df_autos` dataset from statsmodels
ag_autos = AutoGAM(df_autos, 'city_mpg')
# Display the model summary
ag_autos.summary()
# Display the performance metrics
ag_autos.print()
License
autogam
was created by Chitu Okoli. It is licensed under the terms of the MIT license.
Credits
autogam
was created with cookiecutter
and the py-pkgs-cookiecutter
template.
Project details
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