# Data preprocessing
import numpy as np
from sklearn import preprocessing

input_data = np.array([[2.2, -1.9, 5.5],
                      [-1.5, 2.4, 3.5],
                      [5.9, 2.3, -5.8]])

data_binarized = preprocessing.Binarizer(threshold=0.0).transform(input_data)
print(data_binarized)
536e42e50b4fa33753a2d42cd35ff1fb7d091d6c
<mask token>

<mask token>
print(data_binarized)

<mask token>
input_data = np.array([[2.2, -1.9, 5.5], [-1.5, 2.4, 3.5], [5.9, 2.3, -5.8]])
data_binarized = preprocessing.Binarizer(threshold=0.0).transform(input_data)
print(data_binarized)

import numpy as np
from sklearn import preprocessing
input_data = np.array([[2.2, -1.9, 5.5], [-1.5, 2.4, 3.5], [5.9, 2.3, -5.8]])
data_binarized = preprocessing.Binarizer(threshold=0.0).transform(input_data)
print(data_binarized)

# Data preprocessing
import numpy as np
from sklearn import preprocessing

input_data = np.array([[2.2, -1.9, 5.5],
                      [-1.5, 2.4, 3.5],
                      [5.9, 2.3, -5.8]])

data_binarized = preprocessing.Binarizer(threshold=0.0).transform(input_data)
print(data_binarized)