random forest in python code example

Example 1: python random number

from random import randint

print(randint(1,5))

##Possible Outputs##
#1
#2
#3
#4
#5

Example 2: 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]]))

Example 3: how to use random tree in python

from sklearn.ensemble import RandomForestRegressor

regressor = RandomForestRegressor(n_estimators=20, random_state=0)
regressor.fit(X_train, y_train)
y_pred = regressor.predict(X_test)

Example 4: python random number

import random  
#random numbers from 1 to 10
print(random.randint(1,10)) #use of random.randint()

#random word from a list
print(random.choice(["a","b","c","d","e"])) #use of random.choice()

#random shuffle a list
random_list = ["a","b","c","d","e"]
random.shuffle(random_list) #use of random.shuffle()
print(random_list)

Example 5: 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]]))

Example 6: 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)