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Node.js或PHP中的模式识别算法?

[英]Pattern Recognition Algorithms in Node.js or PHP?

I would like to begin experimenting with algorithms that recognize patterns in data. 我想开始尝试识别数据模式的算法。 I deal with many types of sequences (image pixels, text input, user movement), and it would be fun to make use of Pattern Recognition to try to pull meaningful data out of different datasets. 我处理许多类型的序列(图像像素,文本输入,用户移动),使用模式识别尝试从不同的数据集中提取有意义的数据会很有趣。 Like the majority of the web, my data is mostly text or integer-key based. 与大多数网站一样,我的数据主要是基于文本或整数键的。

Are their any classes that give the basic framework for checking/creating patterns for PHP or Nodejs? 他们的任何类都提供了检查/创建PHP或Nodejs模式的基本框架吗?

I've never found a single library that encapsulates different analysis patterns. 我从来没有找到一个封装不同分析模式的库。 You may find specific solutions easily though. 您可以轻松找到具体的解决方案。

N-Gram analysis for example can be done with this PHP extension: http://pecl.php.net/package/TextCat 例如,使用此PHP扩展可以完成N-Gram分析: http//pecl.php.net/package/TextCat

There are several bayes implementations as well, even tutorials. 还有几个bayes实现,甚至是教程。

I've never found Kohonen-nets or self-organizing maps implemented in PHP, but multi-layer perceptrons are trivial. 我从未在PHP中实现Kohonen网或自组织地图,但多层感知器是微不足道的。 IA can do pattern analysis fairily well. IA可以很好地进行模式分析。

There are projects that bind PHP to OpenCV (a library for realtime image/video analysis). 有些项目将PHP绑定到OpenCV(用于实时图像/视频分析的库)。 Currently, the only implementation I know is for detecting human faces in pictures. 目前,我所知道的唯一实现是用于检测图片中的人脸。 The source is open https://github.com/infusion/PHP-Facedetect , so it should be easy to bind other OpenCV goodness (OpenCV can do a lot of stuff with images). 源是开放的https://github.com/infusion/PHP-Facedetect ,因此它应该很容易绑定其他OpenCV的好处(OpenCV可以用图像做很多事情)。

PHP itself is interpreted, most heavy solutions for pattern analysis won't perform well under this limitation. 解释PHP本身,在这种限制下,用于模式分析的大多数重要解决方案都不会很好。 This is why most solutions for this in PHP are written in C as an extension. 这就是为什么PHP中的大多数解决方案都是用C语言编写的扩展。

For machine learning you might consider using a language that is more 'at home' as it'd be easier to express the model.. 对于机器学习,您可能会考虑使用更“在家”的语言,因为它更容易表达模型。

For example the source code for the new 'Machine Learning for Hackers' book, written in R can be found in Github https://github.com/johnmyleswhite/ML_for_Hackers 例如,用R编写的新的“黑客机器学习”一书的源代码可以在Github中找到https://github.com/johnmyleswhite/ML_for_Hackers

And then, there's also the Google Prediction API, which is good for experimenting https://developers.google.com/prediction/docs/developer-guide 然后,还有Google Prediction API,它适用于试验https://developers.google.com/prediction/docs/developer-guide

I realise this is an old question, but since it came at the top of a Google query, it thought it ought to contain a reference to the Node bindings for opencv, node-opencv . 我意识到这是一个老问题,但由于它出现在Google查询的顶部,它认为它应该包含对opencv, node-opencv的Node绑定的引用。

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