Random Forest Classifer

import pandas as pd
import numpy as np
from sklearn.datasets import make_blobs
from sklearn.model_selection import cross_val_score
from sklearn.ensemble import RandomForestClassifier
import matplotlib.pyplot as plt
%matplotlib inline

X, y = make_blobs(n_samples=10000, n_features=10, centers=100, random_state=0)
df_X = pd.DataFrame(X)
df_X.head()

df_y = pd.DataFrame(y, columns=['y'])
df_y.head()

clf = RandomForestClassifier(n_estimators=10, max_depth=None, min_samples_split=2, random_state=0)
scores = cross_val_score(clf, X, y, cv=5, verbose=1)
scores.mean()                               

pd.DataFrame(scores, columns=['CV Scores']).plot();