Efficiently choosing Hyperparameters #2
Description
The hyperparameters chosen now are 90% and 95% based on the rule of thumb. However, based on training data and the domain in which the model is applied, we need to play around with the hyperparameters. Finding appropriate hyperparameters is the most important part of modelling. So we must decide which set of hyperparameters fit the best for each model.