CIFAR-10

CIFAR10_RandomForest_color.py

import numpy as np
import matplotlib.pyplot as plt
from keras.datasets import cifar10
from sklearn.ensemble import RandomForestClassifier
import time

start_time = time.time()
# データの読み込み
(x_train, y_train), (x_test, y_test) = cifar10.load_data()
# 小数化
x_train = x_train / 255
x_test = x_test / 255
# データ数
m_train, m_test = x_train.shape[0], x_test.shape[0]
# ベクトル化
x_train, x_test = x_train.reshape(m_train, -1), x_test.reshape(m_test, -1)
# ランダムフォレストは標準化いらない

# ランダムフォレスト
rf = RandomForestClassifier(max_depth=8)
rf.fit(x_train, y_train)
print("Elapsed[s] : ", time.time() - start_time)
print("Train :", rf.score(x_train, y_train))
print("Test :", rf.score(x_test, y_test))
# デフォルト→Overfitting
#Elapsed[s] :  30.51237440109253
#Train : 0.99394
#Test : 0.3576

# max_depth=8
#Elapsed[s] :  18.324826955795288
#Train : 0.434
#Test : 0.3717#Test : 0.3747