Python classifier_report Beispiele

Beispiel #1

#! /usr/bin/env python3

from classifier import classifier_report
from sklearn.neighbors import KNeighborsClassifier

neighbors = range(1, 8)
for n in neighbors:
    print('----------' + str(n) + ' neighbors ----------')
    classifier_report(KNeighborsClassifier(n_neighbors=n))

Beispiel #2

Datei: meta_adaboost.py Projekt: albertnez/data-mining-pizza

#! /usr/bin/env python3
from classifier import classifier_report
from sklearn.ensemble import AdaBoostClassifier
from sklearn.tree import DecisionTreeClassifier

# Decission tree
print('Decision tree:')
classifier_report(AdaBoostClassifier(DecisionTreeClassifier()))

# Decission stumps
print('Decision stump:')
classifier_report(AdaBoostClassifier(DecisionTreeClassifier(max_depth=1)))

Beispiel #3

Datei: naive_bayes.py Projekt: albertnez/data-mining-pizza

#! /usr/bin/env python3
from classifier import classifier_report
from sklearn.naive_bayes import BernoulliNB

classifier_report(BernoulliNB())

Beispiel #4

Datei: decision_trees.py Projekt: albertnez/data-mining-pizza

#! /usr/bin/env python3
from classifier import classifier_report
from sklearn.tree import DecisionTreeClassifier

classifier_report(DecisionTreeClassifier(max_depth=10))

Beispiel #5

Datei: meta_bagging.py Projekt: albertnez/data-mining-pizza

#! /usr/bin/env python3
from classifier import classifier_report
from sklearn.ensemble import BaggingClassifier
from sklearn.tree import DecisionTreeClassifier

# Decission tree
print('Decision tree:')
classifier_report(BaggingClassifier(base_estimator=DecisionTreeClassifier()))

# Decission stumps
print('Decision stump:')
classifier_report(BaggingClassifier(base_estimator=DecisionTreeClassifier(max_depth=1),n_estimators=100))

Beispiel #6

Datei: knn_classifier.py Projekt: albertnez/data-mining-pizza

#! /usr/bin/env python3

from classifier import classifier_report
from sklearn.neighbors import KNeighborsClassifier

neighbors = range(1,8)
for n in neighbors:
	print('----------' + str(n) + ' neighbors ----------')
	classifier_report(KNeighborsClassifier(n_neighbors=n))

Beispiel #7

#! /usr/bin/env python3
from classifier import classifier_report
from sklearn.svm import SVC

# Polykernel
print('Testing Polykernel')
for d in range(1, 4):
    for c in range(-2, 3):
        cost = 10**c
        print('starting: degree = {0}, cost = {1}'.format(d, cost))
        classifier_report(SVC(kernel='poly', degree=d, C=cost))
        print('finished: degree = {0}, cost = {1}'.format(d, cost))


# Gaussian RBF Kernel
print('Testing RBF')
for g in range(-2, 3):
    for c in range(-2, 3):
        cost = 10**c
        gamma = 10**g
        print('starting: gamma = {0}, cost = {1}'.format(gamma, cost))
        classifier_report(SVC(kernel='rbf', gamma=gamma, C=cost))
        print('finished: gamma = {0}, cost = {1}'.format(gamma, cost))