如何在Python中为数据集编写快速简化降维算法？ [英] How to code a quick reduct dimension reduction algorithm for a dataset in Python?

问题描述

请帮助解决这个问题，我需要尽早提供帮助：

提到的数据集是乳腺癌数据集。

它有11个属性：第1个属性 - 示例代码。

有700个实例。

我需要使用python代码减少它的维度以快速还原算法。



我尝试了什么：



无法使用此方法编码，只是没有得到如何选择属性的可辨别性，即检查每个属性。对于这个主题，不明白这种方法如何比其他降维方法更好。

Please help to solve this, I need help as early as possible:
The dataset mentioned about is the breast cancer dataset.
It has 11 attributes: 1st attribute-sample code number.
There are 700 instances.
I need to reduce it's dimension using python code for quick reduct algorithm .

What I have tried:

Couldn't code using this method,just didn't get how to select indecernibility of attributes i.e. checking each attribute.New to this topic, didn't understand how this method is way better than other methods for dimension reduction.

推荐答案

参见快速还原算法 - Google搜索 [ ^ ]。

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