Source code for mafese.utils.encoder
#!/usr/bin/env python
# Created by "Thieu" at 13:58, 09/05/2023 ----------%
# Email: nguyenthieu2102@gmail.com %
# Github: https://github.com/thieu1995 %
# --------------------------------------------------%
import numpy as np
[docs]class LabelEncoder:
"""
Encode categorical features as integer labels.
"""
def __init__(self):
self.unique_labels = None
self.label_to_index = {}
[docs] def fit(self, y):
"""
Fit label encoder to a given set of labels.
Parameters:
-----------
y : array-like
Labels to encode.
"""
self.unique_labels = np.unique(y)
self.label_to_index = {label: i for i, label in enumerate(self.unique_labels)}
[docs] def transform(self, y):
"""
Transform labels to encoded integer labels.
Parameters:
-----------
y : array-like
Labels to encode.
Returns:
--------
encoded_labels : array-like
Encoded integer labels.
"""
if self.unique_labels is None:
raise ValueError("Label encoder has not been fit yet.")
return np.array([self.label_to_index[label] for label in y])
[docs] def fit_transform(self, y):
"""Fit label encoder and return encoded labels.
Parameters
----------
y : array-like of shape (n_samples,)
Target values.
Returns
-------
y : array-like of shape (n_samples,)
Encoded labels.
"""
self.fit(y)
return self.transform(y)
[docs] def inverse_transform(self, y):
"""
Transform integer labels to original labels.
Parameters:
-----------
y : array-like
Encoded integer labels.
Returns:
--------
original_labels : array-like
Original labels.
"""
if self.unique_labels is None:
raise ValueError("Label encoder has not been fit yet.")
return np.array([self.unique_labels[i] if i in self.label_to_index.values() else "unknown" for i in y])