SVM-w-SMO
所属分类：人工智能/神经网络/深度学习
开发工具：Python
文件大小：49KB
下载次数：6
上传日期：2018-04-10 15:27:41
上 传 者：
brbaaa
说明： 用序列最小优化算法（SMO）进行训练的支持向量机的简单实现。
(simple implementation of a Support Vector Machine using the Sequential Minimal Optimization (SMO) algorithm for training.)
文件列表:
SVM-w-SMO (0, 2018-04-10)
SVM-w-SMO\SVM.pyc (4931, 2018-04-10)
SVM-w-SMO\test.py (2571, 2018-04-10)
SVM-w-SMO\SVM.py (3705, 2018-04-10)
SVM-w-SMO\LICENSE (1087, 2018-04-10)
SVM-w-SMO\data (0, 2018-04-10)
SVM-w-SMO\data\iris-virginica.txt (2608, 2018-04-10)
SVM-w-SMO\data\iris-versicolor.txt (2658, 2018-04-10)
SVM-w-SMO\data\iris-slwc.txt (1460, 2018-04-10)
... ...
# SVM
Simple implementation of a Support Vector Machine using the Sequential Minimal Optimization (SMO) algorithm for training.
## Supported python versions:
* Python 2.7
* Python 3.4
## Python package dependencies
* Numpy (http://docs.scipy.org/doc/numpy-1.10.1/user/install.html)
# Documentation
Setup model (following parameters are default)
```python
from SVM import SVM
model = SVM(max_iter=10000, kernel_type='linear', C=1.0, epsilon=0.001)
```
Train model
```python
model.fit(X, y)
```
Predict new observations
```python
y_hat = model.predict(X_test)
```
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