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import numpy as np
credit_data = np.genfromtxt('./credit_score.txt', delimiter=',', skip_header=True)
# "credit_data" is now a 2d NumPy array. Each rows represent a record and the
# columns represent the data attributes.
# [(22, 0, 0, 28, 1, 0)
# (46, 0, 1, 32, 0, 0)
# (24, 1, 1, 24, 1, 0)
# (25, 0, 0, 27, 1, 0)
# (29, 1, 1, 32, 0, 0)
# (45, 1, 1, 30, 0, 1)
# (63, 1, 1, 58, 1, 1)
# (36, 1, 0, 52, 1, 1)
# (23, 0, 1, 40, 0, 1)
# (50, 1, 1, 28, 0, 1)]
# print(credit_data)
first_row = credit_data[0]
# print('The first row: ', first_row)
fourth_col = credit_data[:,3]
# print('The fourth column: ', fourth_col)
# print(credit_data[...,1:])
# print(credit_data[:3,2])
# print(np.sort(np.unique(credit_data[:,3])))
# print('Total number of examples with binary label 1:', np.sum(credit_data[:,5]))
# print('Sum of all entries in the cols:', credit_data.sum(axis=0))
# print('Select all rows where the first column is bigger than 27:', credit_data[credit_data[:,0] > 27])
x = np.array([2,5,10])
# print(x)
# print(np.arange(0, 10))
# Select the *row numbers* of the rows where the first column of credit_data is bigger than 27:
# print(np.arange(0,10)[credit_data[:,0] > 27])
# Draw a random sample of size 5 from the numbers 1 through 10 (without replacement):
index = np.random.choice(np.arange(0,10), size=5, replace=False)
# print(index)
train = credit_data[index,]
# print(train)
test = np.delete(credit_data, index, axis=0)
# print(test)
# help(np.random.choice)
# Practice exercise1
# test_array = credit_data[:,-1]
test_array = np.array([1,0,1,1,1,0,0,1,1,0,1])
def impurity(array) -> None:
"""
@todo: Docstring for
"""
# print(array)
rel_freq_1_len = len(array[0:])
print('len of the vector:', rel_freq_1_len)
rel_freq_1_sum = array[0:].sum()
print(rel_freq_1_sum)
rel_freq_1 = rel_freq_1_sum / rel_freq_1_len
rel_freq_0 = 1 - rel_freq_1
print('\nThe rel. freq. of 1: ', rel_freq_1)
print('\nThe rel. freq. of 0: ', rel_freq_0)
gini_index = rel_freq_1 * rel_freq_0
print('\nThe gini index: ', gini_index)
# pass
impurity(test_array)
def bestsplit(x,y) -> None:
"""
@todo: Docstring for bestsplit
"""
pass
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