手写字符识别神经网络项目总结
1.数据集
手写字符数据集 DIGITS，该数据集的全称为 Pen-Based Recognition of Handwritten Digits Data Set，来源于 UCI 开放数据集网站。
2.加载数据集
import numpy as np
from sklearn import datasets
digits = datasets.load_digits()
3.分割数据集
from sklearn.model_selection import train_test_split
X, y = digits.data, digits.target
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=30)
4. 搭建人工神经网络
from sklearn.neural_network import MLPClassifier
from sklearn.metrics import accuracy_score
def mpl():
model = MLPClassifier(hidden_layer_sizes=(100, 50), activation='relu', solver='sgd', learning_rate_init=0.02, max_iter=100, random_state=1)
model.fit(X_train, y_train)
y_pred = model.predict(X_test)
score = accuracy_score(y_test, y_pred)
return model, score
5.绘制损失变化曲线
model = mpl()[0]
plt.plot(model.loss_curve_)