What kind of classification or learning algorithm that suits this kind of data exampleenter image description here

If I have to build a model using the given key words then predict column B and then to column A? what kind of algorithm should I use to train and classify the data of this format.

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    $\begingroup$ Can you assume that all the possible target values in column A and B are predefined? And do you have multiple examples for each value in column B? If the answer is no to any of these questions, it's not classification and it's going to be harder. $\endgroup$
    – Erwan
    Aug 16, 2022 at 22:02
  • $\begingroup$ we can consider them to be one C = (A+B) and using key words we can we classify. $\endgroup$
    – User123456
    Aug 17, 2022 at 15:04
  • $\begingroup$ Your answer is not very clear, let me rephrase: if the data is split randomly between training and test set, would there be approximately the same labels in the training and test set, or most labels in the test set would be unique? $\endgroup$
    – Erwan
    Aug 17, 2022 at 17:45
  • $\begingroup$ Yes I have multiple examples for each values in column B. $\endgroup$
    – User123456
    Aug 17, 2022 at 18:14
  • $\begingroup$ Ok so you can use classification then. One of the main question is the choice of text representation, it could be traditional TFIDF or embeddings, depending how large is the vocabulary, how many instances, etc. $\endgroup$
    – Erwan
    Aug 19, 2022 at 14:46

1 Answer 1


When you wonder which algorithm works best for your data, you can try to use some packages like pycaret or H2O .

Documentation for pycaret: https://pycaret.readthedocs.io/en/latest/index.html

Documentation for H2O: https://docs.h2o.ai/h2o/latest-stable/h2o-py/docs/intro.html

When I delt with a multiclass text classification in the past for me support vector classifier and SGD Classifier models worked well. You can also try with an LSTM.


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