https://github.com/myhub/uc
uc 一款专注于数据分析的神经网络
https://github.com/myhub/uc
mlp mlp-classifier mlp-regressor neural-network
Last synced: 3 months ago
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uc 一款专注于数据分析的神经网络
- Host: GitHub
- URL: https://github.com/myhub/uc
- Owner: myhub
- Created: 2020-06-27T00:58:36.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2024-04-29T23:35:53.000Z (about 1 year ago)
- Last Synced: 2025-01-10T15:15:07.246Z (5 months ago)
- Topics: mlp, mlp-classifier, mlp-regressor, neural-network
- Language: Python
- Homepage:
- Size: 11.6 MB
- Stars: 0
- Watchers: 0
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# uc 一款专注于数据分析的神经网络
***Windows*** ***Linux***
## 对比测试
+ [uc.mlp.MLP VS sklearn.neural_network.MLPRegressor
](examples/demo.ipynb)
## 安装
pip install uc
## 功能特性
+ 支持特征重要性
+ 支持缺失值
+ 支持am2/am2l/a2m2/a2m2l激活函数
+ 支持softmax/hardmax/mse/hardmse损失函数
+ 支持fc/add/conv运算
## 第一个例子
# let's use a simple example to learn how to use
from uc.mlp import MLP
import numpy as np
# generate sample
X = np.linspace(-np.pi, np.pi, num=5000).reshape(-1, 1)
Y = np.sin(X)
print(X.shape, Y.shape)
# fit and predict
mlp = MLP(layer_size=[X.shape[1], 8, 8, 8, 1], rate_init=0.02, loss_type="mse", epoch_train=100, epoch_decay=10, verbose=1)
mlp.fit(X, Y)
pred = mlp.predict(X)
# show the result
import matplotlib.pyplot as plt
plt.plot(X, pred)
plt.show()
## 更多示例
+ [分类: iris](examples/iris/)
+ [回归: image painting](examples/image-painting/)
+ [分类: mnist](examples/mnist/)