浅谈Feature Scaling
定义：Feature scaling is a method used to standardize the range of independent variables or features of data. In data processing, it is also known as data normalization and is generally performed during
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相关文章
- 1. Feature Scaling: Normalization and Standardization
- 2. 特征缩放（feature scaling）
- 3. 机器学习（一）- feature scaling
- 4. 特征缩放（Feature Scaling）
- 5. 06-数据归一化（Feature Scaling）
- 6. Dennard scaling(MOSEFT scaling)
- 7. 浅析 Bag of Feature
- 8. 归一化/特征缩放(Feature Scaling) 笔记
- 9. Linear Regression with multiple variables - Gradient descent in practice I: Feature Scaling
- 10. 关于Adaptive Learning Rates(Adagrad)与Feature Scaling的理解