import numpy as np
from sklearn.model_selection import train_test_split
from itertools import combinations
from sklearn.linear_model import LinearRegression

list1 = [12, 20, 37, 41, 64, 1, 3, 10, 22, 65, 66, 19, 5, 11, 41, 44, 55, 14, 15, 34, 36, 69, 70, 17, 1, 2, 23, 40, 45, 15, 4, 37, 46, 48, 51, 19, 16, 18, 28, 42, 43, 11, 3, 15, 16, 32, 41, 9, 18, 38, 53, 62, 64, 20, ]
list2 = [8, 25, 36, 39, 67, 11, 14, 16, 40, 52, 59, 13, 2, 22, 49, 65, 67, 7, 23, 24, 35, 40, 43, 1, 2, 33, 38, 57, 70, 13, 23, 24, 35, 40, 43, 1, 20, 29, 30, 52, 58, 19, 9, 15, 46, 55, 57, 4, 1, 40, 50, 54, 59, 18, 7, 9, 18, 29, 39, 13, 20, 29, 31, 64, 66, 17, 33, 41, 47, 50, 62, 20, 20, 29, 31, 64, 66, 17]



# Split the data into X and y
X = list1
y = list2



X = np.array(list1).reshape(-1, 1)

y = np.array(list2).reshape(-1, 1)
# Define the input numbers
input_numbers = np.array([13, 16, 40, 64, 68, 21]).reshape(1, -1)

# Train the model
model = LinearRegression()
model.fit(X, y)

# Make predictions for each combination of input numbers
for combination in itertools.combinations(input_numbers, 8):
    predictions = model.predict(np.array(combination).reshape(1, -1))
    print(combination)
    print(predictions). 
    File "C:/Users/moder/AppData/Local/Programs/Python/Python310/LP v7.1.py", line 26, in <module>
    model.fit(X, y)
  File "C:\Users\moder\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\linear_model\_base.py", line 648, in fit
    X, y = self._validate_data(
  File "C:\Users\moder\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\base.py", line 584, in _validate_data
    X, y = check_X_y(X, y, **check_params)
  File "C:\Users\moder\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\utils\validation.py", line 1124, in check_X_y
    check_consistent_length(X, y)
  File "C:\Users\moder\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\utils\validation.py", line 397, in check_consistent_length
    raise ValueError(
ValueError: Found input variables with inconsistent numbers of samples: [54, 78]