Classificadores Lineares em Python
Michael (Mike) Gelbart
Instructor, The University of British Columbia



$\textrm{transformed feature} =$
$ (\textrm{original feature})^2$

$\textrm{transformed feature} =$
$ (\textrm{original feature})^2$


$\textrm{transformed feature} =$
$ (\textrm{original feature})^2$
from sklearn.svm import SVC
svm = SVC(gamma=1) # default is kernel="rbf"

from sklearn.svm import SVC
svm = SVC(gamma=0.01) # default is kernel="rbf"

gamma menor gera fronteiras mais suavesfrom sklearn.svm import SVC
svm = SVC(gamma=2) # default is kernel="rbf"

gamma maior gera fronteiras mais complexasClassificadores Lineares em Python