Advanced Data Analytics Using Python_ With Machine Learning, Deep Learning and NLP Examples ( 2023)

Chapter 3
Supervised Learning Using Python
to find two parallel hyperplanes that separate the data. This planes are
known as the margin. The algorithm chose the margins in such a way that
the distance between them is the maximum. That’s why it is the maximum
margin. The plane, which is at the middle of these two margins or at equal
distance between them, is known as an optimal hyperplane that is used to
classify the test data (see Figure 3-2). The separator can be nonlinear also.
X 2
X 1
Optimal hyperplane
Maximum
margin
Figure 3-2. Support vector machine
The following code is an example of doing support vector machine
classification using Python:
from sklearn import svm
df = pd.read_csv('csv file path', index_col=0)
y = df[target class column ]
X = df[ col1, col2 ..]
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