lssvr is a Python module implementing the Least Squares Support Vector Regression using the scikit-learn as base.
Example:
import numpy as np
from lssvr import LSSVR
from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
boston = load_boston()
X_train, X_test, y_train, y_test = train_test_split(boston.data, boston.target, test_size=0.2)
model = LSSVR()
model.fit(X_train, y_train, kernel='linear')
y_hat = model.predict(X_test)
print('LSSVR\nMSE', mean_squared_error(y_test, y_hat))
print('R2 ',model.score(X_test, y_test))