Handling High Variance
For handling issues of high variance, we should use the bagging algorithm.
Bagging algorithm would split data into sub-groups with replicated sampling of random data.
Once the algorithm splits the data, we use random data to create rules using a particular training algorithm.
After that, we use polling for combining the predictions of the model.