Sklearn random forest regressor

from sklearn.ensemble import RandomForestRegressor


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

clf.fit(X, y)

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

How to use random tree in python

from sklearn.model_selection import train_test_split

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

Source: stackabuse.com

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]]))

Similar codes

0 vote146 views1 answer
If we use list in the dictionary
Python
1 vote156 views1 answer
Conda install lxml
Python
0 vote171 views1 answer
Python paramiko
Python
11 votes173 views1 answer
Scikit learn svm
Python
1 vote160 views1 answer
Python new line character in string
Python
3 votes181 views3 answers
NameError: name ‘pd’ is not defined
Python
3 votes208 views1 answer
For e in p.event.get(): pygame.error: video system not initialized
Python
0 vote171 views1 answer
Location of matploitlibrc file
Python
0 vote184 views1 answer
Cv2 check if image is grayscale
Python
1 vote181 views1 answer
Python scond max function
Python