如何在Open CV LibSVM中扩展数据 [英] How to scale data in Open CV LibSVM

问题描述

我正在开发英文手写OCR。我使用基于区域的方法进行特征提取。在这里，我使用64 X 64图像。

所以我有一个样本图像的64个功能。我的SVM将是多级SVM，因为我有52个大写字母和简单字母。

这是特征向量的格式。



A类图像1 0：0.222000 1：0.0250222 ..... 63：0.000052

A类图像2（一些浮动值）....

A类图像400 （一些漂浮值）



同样我有52个类的400张图像。我读过缩放数据可以提高预测的准确性。

但是我还有一些事情需要说清楚。



01.如何缩放这些特征值？



02.是否有任何函数可以获得Open CV LibSVM中每个测试特征向量的匹配概率？



（我搜索Open CV 2.4.5文档，但我找不到这个）



有人可以解释这些吗？如果可能的话，还有一些代码行。



谢谢

i am developing English Handwriting OCR. I use Zone based approach for feature extraction. Here I use 64 X 64 images.
So i have 64 features for one sample image. My SVM will be Multi-class SVM because i have 52 classes for both capital and simple letters.
Here is the format of feature vector.

Class A image1 0 : 0.222000 1 : 0.0250222 ..... 63 : 0.000052
Class A image2 (some float values) ....
Class A image400 (some float values)

likewise i have 400 images for both 52 classes. I have read as scaling data increase the accuracy of the prediction.
But i have few things to be make clear.

01. How can i scale these feature values ?

02. Is there any function to get the matching probability of each test feature vector in Open CV LibSVM?

(i search the Open CV 2.4.5 documentation, but i couldn't find this)

can anyone explain these? , and also with some few code lines if possible.

Thank you

推荐答案

大家好，<发现缩放数据意味着，将所有训练和测试数据保持在0 - 1或-1 - +1等范围内。


i我将继续这样做。有没有人有任何想法或建议，请在这里评论。谢谢

hi all,

i found scaling data means , keep all training and testing data within a range such as 0 - 1 or -1 - +1. i will proceed with that. does anyone has any idea or suggestion, please comment it here. thank you

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