莫烦python教程学习笔记——validation_curve用于调参
2024-10-11 06:55:36
# View more python learning tutorial on my Youtube and Youku channel!!! # Youtube video tutorial: https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg
# Youku video tutorial: http://i.youku.com/pythontutorial """
Please note, this code is only for python 3+. If you are using python 2+, please modify the code accordingly.
"""
from __future__ import print_function
from sklearn.learning_curve import validation_curve
from sklearn.datasets import load_digits
from sklearn.svm import SVC
import matplotlib.pyplot as plt
import numpy as np digits = load_digits()
X = digits.data
y = digits.target
param_range = np.logspace(-6, -2.3, 5)
train_loss, test_loss = validation_curve(
SVC(), X, y, param_name='gamma', param_range=param_range, cv=10,
scoring='mean_squared_error')
train_loss_mean = -np.mean(train_loss, axis=1)
test_loss_mean = -np.mean(test_loss, axis=1) plt.plot(param_range, train_loss_mean, 'o-', color="r",
label="Training")
plt.plot(param_range, test_loss_mean, 'o-', color="g",
label="Cross-validation") plt.xlabel("gamma")
plt.ylabel("Loss")
plt.legend(loc="best")
plt.show()
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