What are the steps to follow when building a text classification syste

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.

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.