Support Vector Regression

preprocessing

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

dataset = pd.read_csv('_data/04.csv')
x = dataset.iloc[:, 1:-1].values
y = dataset.iloc[:, -1].values
y = y.reshape(len(y), 1)

from sklearn.preprocessing import StandardScaler

sc_x = StandardScaler()
sc_y = StandardScaler()

x = sc_x.fit_transform(x)
y = sc_y.fit_transform(y)

Train

from sklearn.svm import SVR

regressor = SVR(kernel='rbf')
regressor.fit(x, y)

/home/cryscham123/.local/lib/python3.12/site-packages/sklearn/utils/validation.py:1339: DataConversionWarning:

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().

SVR()

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Visualize

plt.scatter(sc_x.inverse_transform(x), sc_y.inverse_transform(y), color='red')
plt.plot(sc_x.inverse_transform(x), sc_y.inverse_transform(regressor.predict(x).reshape(-1, 1)))
plt.show()

High resolution

x_grid = np.arange(min(sc_x.inverse_transform(x)), max(sc_x.inverse_transform(x)), 0.1)
x_grid = x_grid.reshape((len(x_grid), 1))
plt.scatter(sc_x.inverse_transform(x), sc_y.inverse_transform(y), color='red')
plt.plot(x_grid, sc_y.inverse_transform(regressor.predict(sc_x.transform(x_grid)).reshape(-1, 1)))
plt.show()

/tmp/ipykernel_12503/1939094151.py:1: DeprecationWarning:

Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)