from sklearn import tree
from sklearn import svm
from sklearn.linear_model import SGDClassifier

#[height, weight, shoe size]
X = [[181,80,44], [177, 70, 43], [160, 60, 38], [154, 54, 37],
	[166,65,40], [190,90,47], [175,64,39], [177,70,40], [159,55,37],
	[171,75,42], [181,85,43]]

Y = ['male', 'female', 'female', 'female','male', 'male', 'male', 'female', 'male', 'female', 'male']


#tree
clf = tree.DecisionTreeClassifier()

#svm
clf1 = svm.SVC()

#SGDC
clf2 = SGDClassifier()


#tree
clf = clf.fit(X,Y)

#svm
clf1 = clf1.fit(X,Y)

#SGDC
clf2 = clf2.fit(X,Y)


#tree
predicition1 = clf.predict([[190,70,43]])

#svm
predicition2 = clf1.predict([[190,70,43]])

#SGDC
predicition3 = clf2.predict([[190,70,43]])


#print tree
print("From tree: ", predicition1, "\n")

#print svm
print("From svm: ", predicition2, "\n")

#print SGDC
print("From SGDC: ", predicition3, "\n")
4b6cd19331286d424a88cfdf881b745f8b9ba326
<mask token>

<mask token>
print('From tree: ', predicition1, '\n')
print('From svm: ', predicition2, '\n')
print('From SGDC: ', predicition3, '\n')

<mask token>
X = [[181, 80, 44], [177, 70, 43], [160, 60, 38], [154, 54, 37], [166, 65, 
    40], [190, 90, 47], [175, 64, 39], [177, 70, 40], [159, 55, 37], [171, 
    75, 42], [181, 85, 43]]
Y = ['male', 'female', 'female', 'female', 'male', 'male', 'male', 'female',
    'male', 'female', 'male']
clf = tree.DecisionTreeClassifier()
clf1 = svm.SVC()
clf2 = SGDClassifier()
clf = clf.fit(X, Y)
clf1 = clf1.fit(X, Y)
clf2 = clf2.fit(X, Y)
predicition1 = clf.predict([[190, 70, 43]])
predicition2 = clf1.predict([[190, 70, 43]])
predicition3 = clf2.predict([[190, 70, 43]])
print('From tree: ', predicition1, '\n')
print('From svm: ', predicition2, '\n')
print('From SGDC: ', predicition3, '\n')

from sklearn import tree
from sklearn import svm
from sklearn.linear_model import SGDClassifier
X = [[181, 80, 44], [177, 70, 43], [160, 60, 38], [154, 54, 37], [166, 65, 
    40], [190, 90, 47], [175, 64, 39], [177, 70, 40], [159, 55, 37], [171, 
    75, 42], [181, 85, 43]]
Y = ['male', 'female', 'female', 'female', 'male', 'male', 'male', 'female',
    'male', 'female', 'male']
clf = tree.DecisionTreeClassifier()
clf1 = svm.SVC()
clf2 = SGDClassifier()
clf = clf.fit(X, Y)
clf1 = clf1.fit(X, Y)
clf2 = clf2.fit(X, Y)
predicition1 = clf.predict([[190, 70, 43]])
predicition2 = clf1.predict([[190, 70, 43]])
predicition3 = clf2.predict([[190, 70, 43]])
print('From tree: ', predicition1, '\n')
print('From svm: ', predicition2, '\n')
print('From SGDC: ', predicition3, '\n')

from sklearn import tree
from sklearn import svm
from sklearn.linear_model import SGDClassifier

#[height, weight, shoe size]
X = [[181,80,44], [177, 70, 43], [160, 60, 38], [154, 54, 37],
	[166,65,40], [190,90,47], [175,64,39], [177,70,40], [159,55,37],
	[171,75,42], [181,85,43]]

Y = ['male', 'female', 'female', 'female','male', 'male', 'male', 'female', 'male', 'female', 'male']


#tree
clf = tree.DecisionTreeClassifier()

#svm
clf1 = svm.SVC()

#SGDC
clf2 = SGDClassifier()


#tree
clf = clf.fit(X,Y)

#svm
clf1 = clf1.fit(X,Y)

#SGDC
clf2 = clf2.fit(X,Y)


#tree
predicition1 = clf.predict([[190,70,43]])

#svm
predicition2 = clf1.predict([[190,70,43]])

#SGDC
predicition3 = clf2.predict([[190,70,43]])


#print tree
print("From tree: ", predicition1, "\n")

#print svm
print("From svm: ", predicition2, "\n")

#print SGDC
print("From SGDC: ", predicition3, "\n")