It looks like you're new here. If you want to get involved, click one of these buttons!
noah977 wrote:I've read that this makes sense because It is less error (safer) for the classifier to simply mark everything negative with such unbalanced data.
A person who really understands data and analysis will understand all the pitfalls and limitations, and hence be constantly caveating what they say. Somebody who is simple, straightforward, and 100% certain usually has no idea what they are talking about.
RapidMiner Auto Model
RapidMiner Turbo Prep
Training Classes & Certification
ML Algorithm Reference
Educational License Program