import os
path="/home/samrat/Documents/Git/PYTHON/SKLEARN/SVM"
os.chdir(path)
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC
from adspy_shared_utilities import (plot_class_regions_for_classifier_subplot)
X_train, X_test, y_train, y_test = train_test_split(X_C2, y_C2, random_state = 0)
fig, subaxes, = plot.subplots(1,1,figsize=(7,5))
this_C = 1.0
clf = SVC(kernel='linear', C=this_C).fit(X_train, y_train)
title = 'Linear SVC, C = {:.3f}'.format(this_C)
plot_class_regions_for_classifier_subplot(clf, X_train, y_train, None, None, title, subaxes)

ab30988e9c58c8624203b437f98d414f20c57f30
<mask token>

<mask token>
os.chdir(path)
<mask token>
plot_class_regions_for_classifier_subplot(clf, X_train, y_train, None, None,
    title, subaxes)

<mask token>
path = '/home/samrat/Documents/Git/PYTHON/SKLEARN/SVM'
os.chdir(path)
<mask token>
X_train, X_test, y_train, y_test = train_test_split(X_C2, y_C2, random_state=0)
fig, subaxes = plot.subplots(1, 1, figsize=(7, 5))
this_C = 1.0
clf = SVC(kernel='linear', C=this_C).fit(X_train, y_train)
title = 'Linear SVC, C = {:.3f}'.format(this_C)
plot_class_regions_for_classifier_subplot(clf, X_train, y_train, None, None,
    title, subaxes)

import os
path = '/home/samrat/Documents/Git/PYTHON/SKLEARN/SVM'
os.chdir(path)
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC
from adspy_shared_utilities import plot_class_regions_for_classifier_subplot
X_train, X_test, y_train, y_test = train_test_split(X_C2, y_C2, random_state=0)
fig, subaxes = plot.subplots(1, 1, figsize=(7, 5))
this_C = 1.0
clf = SVC(kernel='linear', C=this_C).fit(X_train, y_train)
title = 'Linear SVC, C = {:.3f}'.format(this_C)
plot_class_regions_for_classifier_subplot(clf, X_train, y_train, None, None,
    title, subaxes)

import os
path="/home/samrat/Documents/Git/PYTHON/SKLEARN/SVM"
os.chdir(path)
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC
from adspy_shared_utilities import (plot_class_regions_for_classifier_subplot)
X_train, X_test, y_train, y_test = train_test_split(X_C2, y_C2, random_state = 0)
fig, subaxes, = plot.subplots(1,1,figsize=(7,5))
this_C = 1.0
clf = SVC(kernel='linear', C=this_C).fit(X_train, y_train)
title = 'Linear SVC, C = {:.3f}'.format(this_C)
plot_class_regions_for_classifier_subplot(clf, X_train, y_train, None, None, title, subaxes)
