Learn practical skills, build real-world projects, and advance your career

scikit-learn-svm

Credits: Forked from PyCon 2015 Scikit-learn Tutorial by Jake VanderPlas

  • Support Vector Machine Classifier
  • Support Vector Machine with Kernels Classifier
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import seaborn; 
from sklearn.linear_model import LinearRegression
from scipy import stats
import pylab as pl

seaborn.set()

Support Vector Machine Classifier

Support Vector Machines (SVMs) are a powerful supervised learning algorithm used for classification or for regression. SVMs draw a boundary between clusters of data. SVMs attempt to maximize the margin between sets of points. Many lines can be drawn to separate the points above: