What can be done to increase the accuracy of a biological dataset? I have a biological unbalanced dataset on which I have applied deep learning, Support Vector Machine (all the kernel functions) and Artificial Neural network for multiclass classification (size: 139 samples , 5 attributes) in python. Unfortunately the accuracy is not exceeding 55%. What can be done to increase the accuracy? If a dataset cannot ever go beyond such an average accuracy, what is the solution?
There are many possible explanations.
Maybe just mistakes in the code or maybe there is just no better separation possible.
When usign SVM the features are extremely important and you should most of your time invest in choosing/designing them.
The statement &quot;I have applied Deep learning&quot; ist just to vague and therefore I can not give any tip.
Third when dealing with unbalanced data you have many possible actions.
I recommend reading:
Oversampling and undersampling in data analysis