Model Training & Adaptation
Voting classifier
Combining several systems' group predictions into a shared choice, using votes or estimated chances.
Example
Several AI systems vote on whether an email is spam.
Why people use it
It combines several classifiers' choices into one decision.
What you'll hear
“Let the predictors vote on the category.”
What this means for you
Test rare message types as well as common ones.
Can you control it?
Developer-only
The people building or running the AI choose this setup. An everyday user generally needs their help to change how this part works.
Common questions
- Can several systems agree and still be wrong?
- Yes. Shared learning material or similar designs can lead them to make the same mistake.
- Does every vote have to carry equal weight?
- No. Some combinations give more influence to selected predictors.
- Can it combine probabilities instead of hard choices?
- Yes. Some voting approaches average probability estimates rather than only count category votes.