lssvr

Least Squares Support Vector Regression


Keywords
machine-learning, data-science, lssvr, regression, hacktoberfest, lssvm
License
MIT
Install
pip install lssvr==0.1.0

Documentation

lssvr

lssvr is a Python module implementing the Least Squares Support Vector Regression using the scikit-learn as base.

basic usage

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))