1.

What are the steps to follow when building a text classification system?

Answer»

When creating a text classification system, the following steps are usually followed:

  • Gather or develop a labelled DATASET that is appropriate for the purpose.
  • Decide on an evaluation metric after splitting the dataset into two (TRAINING and test) or three PARTS: training, validation (i.e., development), and test SETS (s).
  • Convert unprocessed text into feature vectors.
  • Utilize the feature vectors and labels from the training set to train a classifier.
  • Benchmark the model's performance on the test set using the evaluation metric(s) from Step 2.
  • Deploy the model and TRACK its performance to serve a real-world use case.


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