title: How precise can ML classifiers be?
body: <p>Before tagging thousands of comments and evaluating several ML classifiers I'm curious whether ML classifiers should even be used on the problem below. I've searched the web and stack overflow and only received definitions for precision, recall, accuracy, etc. which is not what I'm looking for. </p>
  
  <p>I need to retrieve customer comments that belong to particular categories so that we know where to make improvements. For example, we need to see the comments regarding "damaged products". The problem is that customers, as you would expect, enter positive comments and negative comments that are very similar. </p>
  
  <p>Lets say we have a series of comments like the following (abbreviated for example)</p>
  
  <p>Negative examples:</p>
  
  <ul>
  <li>received a product with damage</li>
  <li>very badly damaged product</li>
  <li>much damage to this item</li>
  </ul>
  
  <p>Very similar positive examples:</p>
  
  <ul>
  <li>received a product with no damage</li>
  <li>very good product no damage</li>
  <li>no damage to this item</li>
  </ul>
  
  <p>Can ML classifiers be trained to identify samples with a high degree of certainty even when the text to be classified is very similar? </p>
  
  <p>Thanks. </p>