如何对未标记的数据进行分类？

Question

I am new to Machine Learning. I am trying to build a classifier that classifies the text as having a url or not having a url. The data is not labelled. I just have textual data. I don't know how to proceed with it. Any help or examples is appreciated.

Answer 1

1. You cannot train a classifier with unlabeled data. You need labeled examples. There are services that will label it for you, but it might be simpler for you to do it by hand (I assume you can go through one per minute).
2. Stack Overflow is for programming; this question would be better suited in, say, Cross-Validated . Maybe they'll have better suggestions than me.
3. After you've labeled the data, there's a lot of info on the web on this subject - for example, this blog is a good place to start if you already have some grip on the issue.

Good luck!

Answer 2

Since it's text, you can use bag of words technique to create vectors.

• You can use cosine similarity to cluster the common type text.

• Then use classifier, which would depend on number of clusters.

• This way you have a labeled training set.

  • If you have two cluster, binary classifier like logistic regression would work.
  • If you have multiple classes, you need to train model based on multinomial logistic regression
  • or train multiple logistic models using One vs Rest technique.

• Lastly, you can test your model using k-fold cross validation.