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The variables include categorical variables like (contains video, author) and numerical variables like (average word length) and a text (combination of words).

I am confused about this because from what I understand only regression can be used to predict continuous variable. However, I was thinking of forming a bag of words array for the text and title and I do have other categorical variables so i am not sure which model would be ideal. Which ML model would be the best to predict a continuous variable?

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  • $\begingroup$ The usual machine learning models can do regression. Support vectors, random forests, and neural networks all have regression variants. $\endgroup$
    – Dave
    Commented Jun 30, 2021 at 1:01

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I believe this is what you want to know, the approach to handle your text data. You can do one hot encoding for your categorical data if they are not ordinal or label encoding for ordinal. As for model, I am also a newbie but I think you can't define a rule of thumb that this model is best for regression. It depends on the data, which model will work.

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