# Class imbalance problem?

While working with 3 classes,my dataset contains different proportions of all classes. For example,

Class "0"  has  11098 cases.....Normal
class  "1" has  2369 cases....."Abnormal"
class  "2" has  3396 cases....."May be Normal or Abnormal"


I trained the model with similar proportions. I have two questions:

• Is it necessary to balance all three classes?

• What is the impact of class imbalance on classification performance?

• Your data is fairly balanced. Don't worry about it. If you are, try adjusting the decision threshold or loss function. I'm more concerned about your representation; is "May be Normal or Abnormal" one of the classes? Are you using some other signal to infer the ground truth; what's going on? – Emre May 24 '17 at 6:10
• @Emre...Yes...I extracted my dataset from signals...to see the faulty/No faulty status – Case Msee May 24 '17 at 7:09