Saving and loading models can be desired to start from a previous learning point. In order to accomplish this, two functions are implemented: function distfit.save() and function distfit.load() Below is an illustration how to save and load models.

Saving

Saving a learned model can be done using the function distfit.save():

from distfit import distfit
import numpy as np
# Example data
X = np.random.normal(0, 2, 5000)
y = [-8,-6,0,1,2,3,4,5,6]

dfit = distfit()
dfit.fit_transform(X)
dfit.predict(y)

# Save model
dfit.save('my_first_model.pkl')

Loading

Loading a learned model can be done using the function dfit.load():

# Initialize
dfit = distfit()

# Load model
dfit.load('my_first_model.pkl')

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