title: How to identify if a variable should be considered categorical or not while building and training machine learning model?
body: <p>I have a dataset in which there are 10,000 rows in total and 11 features (customerId, firstVisitDate, secondVisitDate, articleId, section, author, headline, topicKeywords, totalVisits, wordCount, and videoCount).</p>
  <p>I am building a machine learning model with the features above predicting the likelihood of a first-time visitor returning to the article. In other words, the likelihood of a first-time visitor of an article converting into a second-time visitor of the same article.</p>
  <p>In this problem, I would need to take articleId as a feature to train the model with other important features BUT articleId is a string variable that has 1206 unique values.</p>
  <p>Question: Would it be reasonable to consider articleId with 1206 unique values as a categorical variable and then do dummy encoding of it? How to tackle this problem. Any feedback how this can be done in a better way.</p>
  <p>Link to the dataset: <a href="https://drive.google.com/file/d/1EkLxsZgXhLhS6_8eoc-rhDOzAzltyeri/view?usp=sharing" rel="nofollow noreferrer">https://drive.google.com/file/d/1EkLxsZgXhLhS6_8eoc-rhDOzAzltyeri/view?usp=sharing</a></p>