title: Difference between model accuracy from test data and confusion matrix accuracy
body: <ul>
  <li>I am working for NLP project where I wanted to do text classification
  using neural n/w</li>
  <li>I am getting very nice accuracy from the test set as 98%.</li>
  <li>But, when I tried to check the confusion matrix accuracy (the accuracy score using confusion matrix) it's just 52%.</li>
  <li>How is it possible? What am I missing here? </li>
  </ul>
  
  <h1>Question</h1>
  
  <p>What is the difference between both the accuracy's which one should be considered as the actual accuracy? and why?</p>
  
  <h1>Code on test set</h1>
  
  <pre><code>loss, acc = model.evaluate(Xtest, y_test_array)
  </code></pre>