# What will cause high accuracy but a big loss?

In the question of What is the relationship between the accuracy and the loss in deep learning?, @Jérémy Blain gave a fantastic interpretation of 'relationship' between accuracy and loss:

• 1 - low accuracy and big loss means you made huge errors on a lot of data
• 2 - low accuracy but small loss means you made little errors on a lot of data
• 3 - high accuracy with small loss means you made low errors on a few data (best case)
• 4 - high accuracy but a big loss, means you made huge errors on a few data.

As I understand,

• 1 - implies bad algorithm 'in most of time'
• 2 - implies overfitting
• 3 - is what we want

Questions are:

 1   Any other reasons caused 1 and 2?
2   what will lead to case 4 : high accuracy but a big loss?

• Regarding your question no.2 - it means that the model is very good, well predicts almost all instances, but there are some outliers of a huge impact on the loss. – Grzegorz Sionkowski Dec 16 '19 at 10:47
• @GrzegorzSionkowski,thanks,outliers will be big reason for high acc but big loss. – Alex Luya Dec 16 '19 at 11:35