将大量分类变量编码为输入数据 [英] Encoding large numbers of categorical variables as input data

问题描述

在处理数百个类别(例如，列之一为名字"的数据集.编码此类数据的最佳方法是什么?

One hot encoding doesn't sound like a great idea when you're dealing with hundreds of categories e.g. a data set where one of the columns is "first name". What's the best approach to go about encoding this sort of data?

推荐答案

我建议使用哈希技巧:

https://en.wikipedia.org/wiki/Feature_hashing#Feature_vectorization_using_the_hashing_trick

计算便宜，易于使用，允许您指定维数，并且通常用作分类的良好基础.

It's cheap to compute, easy to use, allows you to specify the dimensionality, and often serves as a very good basis for classification.

对于您的特定应用程序，我将对特征/值对(例如('FirstName'，'John')进行哈希处理，然后增加该哈希值的存储桶.

For your specific application, I would hash feature-value pairs, like ('FirstName','John'), then increment the bucket for the hashed value.

这篇关于将大量分类变量编码为输入数据的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！