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