The best way to calculate classification accuracy?
<p>I know one formula to calculate classification accuracy is <strong>X = t / n * 100</strong> (where t is the number of correct classification and n is the total number of samples. )</p>

<p>But, let's say we have total 100 samples, 80 in class A, 10 in class B, 10 in class C.</p>

<p><strong>Scenario 1:</strong> All 100 samples were assigned to class A, by using the formula, we got accuracy equals 80%.</p>

<p><strong>Scenario 2:</strong> 10 samples belong to B were correctly assigned to class B ;10 samples belong to C were correctly assigned to class C as well; 30 samples belong to A correctly assigned to class A; the rest 50 samples belong to A were incorrectly assigned to C. By using the formula, we got accuracy of 50%.</p>

<p>My question is:</p>

<p>1: Can we say scenario 1 has a higher accuracy rate then scenario 2?</p>

<p>2: Is there any way to calculate accuracy rate for classification problem?</p>

<p>Many thanks ahead!</p>