分类时跳过特征，但在输出中显示特征 [英] Skip feature when classifying, but show feature in output

问题描述

我创建了一个包含 +/- 13000 行和 +/- 50 个特征的数据集.我知道如何输出每个分类结果:预测和实际，但我希望能够用这些结果输出某种 ID.所以我在我的数据集中添加了一个 ID 列，但我不知道在分类时如何忽略 ID，同时仍然能够输出每个预测结果的 ID.我知道如何选择要在每次预测中输出的特征.

I've created a dataset which contains +/- 13000 rows with +/- 50 features. I know how to output every classification result: prediction and actual, but I would like to be able to output some sort of ID with those results. So i've added a ID column to my dataset but I don't know how disregard the ID when classifying while still being able to output the ID with every prediction result. I do know how to select features to output with every prediction.

推荐答案

使用 FilteredClassifier.请参阅this 和 this .

Use FilteredClassifier. See this and this .

这篇关于分类时跳过特征，但在输出中显示特征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！