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""" | |
Filename: _2_scale_transform.py <br> | |
Title: Custom scale transformer for new user input <br> | |
Author: Raghava | GitHub: @raghavtwenty <br> | |
Date Created: June 10, 2023 | Last Updated: May 13, 2024 <br> | |
Language: Python | Version: 3.10.14, 64-bit <br> | |
""" | |
# Importing required library | |
import numpy as np | |
# Transformation function | |
def transform_new_input(new_input): | |
# Scaled minimum and maximum values from preprocessing | |
scaled_min = np.array( | |
[ | |
1.0, | |
10.0, | |
856.0, | |
5775.0, | |
42.0, | |
26.0, | |
0.0, | |
278.0, | |
4.0, | |
1.0, | |
-630355.0, | |
4.0, | |
50.0, | |
] | |
) | |
scaled_max = np.array( | |
[ | |
4.0, | |
352752.0, | |
271591638.0, | |
239241314.0, | |
421552.0, | |
3317.0, | |
6302708.0, | |
6302708.0, | |
5.0, | |
5.0, | |
1746749.0, | |
608.0, | |
1012128.0, | |
] | |
) | |
new_input = np.array(new_input) | |
# Formula for transformation | |
scaled_input = (new_input - scaled_min) / (scaled_max - scaled_min) | |
return scaled_input | |
# Main | |
if __name__ == "__main__": | |
# Test case | |
test_input = [ | |
[2, 209, 20671, 6316631, 274, 96, 3527, 2757949, 5, 2, 183877, 8, 90494] | |
] | |
print("Scaled value: ") | |
print(transform_new_input(test_input)) | |