/Python/Scikit learn random forest classifier

Scikit learn random forest classifier

Sklearn random forest

from sklearn.ensemble import RandomForestClassifier


clf = RandomForestClassifier(max_depth=2, random_state=0)

clf.fit(X, y)

print(clf.predict([[0, 0, 0, 0]]))

Sklearn random forest

from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import make_classification


X, y = make_classification(n_samples=1000, n_features=4,
                            n_informative=2, n_redundant=0,
                            random_state=0, shuffle=False)
clf = RandomForestClassifier(max_depth=2, random_state=0)

clf.fit(X, y)

print(clf.predict([[0, 0, 0, 0]]))

Scikit learn random forest

from sklearn.ensemble import BaggingClassifier
from sklearn.neighbors import KNeighborsClassifier
bagging = BaggingClassifier(KNeighborsClassifier(),
                            max_samples=0.5, max_features=0.5)

Source: scikit-learn.org

Scikit learn random forest classifier

from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import make_classification


X, y = make_classification(n_samples=1000, n_features=4,
                            n_informative=2, n_redundant=0,
                            random_state=0, shuffle=False)
clf = RandomForestClassifier(max_depth=2, random_state=0)

clf.fit(X, y)

print(clf.predict([[0, 0, 0, 0]]))

-1

Similar codes

0 vote132 views1 answer
Fastest clicker python
Python
1 vote144 views2 answers
Python dequeu
Python
17 votes140 views5 answers
Python input integer
Python
1 vote167 views2 answers
Join two querysets django
Python Django
167 votes223 views6 answers
Pip upgrade package
Python
75 votes144 views2 answers
Pythonwrite to file
Python
0 vote165 views1 answer
Image_file = models.ImageField(upload_to='images') image_url = models.URLField()
Python
0 vote139 views1 answer
Travis ci .yml for python
Python
0 vote182 views1 answer
Numpy convolution stride tricks
Python
1 vote107 views1 answer
Not bitwise operator python
Python