What is the exact definition for "imbalanced datasets" or "imbalanced learning"? Some article states it as,
In such problems, almost all the instances are labeled as one class, while far fewer instances are labeled as the other class, usually the more important class.
While some other article, like Neelam Rout (2018) says,
The ratio between the majority and minority classes may be 100:1, 1000:1 and 10000:1; in short, the instances of majority class outnumber the amount of minority class instances.
I have a dataset with 85% labeled positive and the others negative. Is it an imbalanced dataset?