If you train 10 distinct models on the same training data, try integrating them into a voting ensemble, which will eventually produce better results.
Voting is an ensemble technique for making predictions by combining the results of various models. The predictive performance of an ensemble is better than that of a single predictive model in a predictive modeling issue. This is accomplished by the model adding bias, which lowers the variance component of the prediction error
calculation
Voting ensembles frequently produce even better results, so try combining them.
The models should differ greatly for it to operate. 95 percent accuracy.
We will therefore get better results if we combine them.
If you train 10 distinct models on the same training data, try integrating them into a voting ensemble, which will eventually produce better results.
To know more about voting ensemble visit :-
https://brainly.com/question/18364291
#SPJ4
