One of the core tasks in developing ML models is choosing the ML algorithm and configuring the parameters of the algorithm. ML Studio provides modules for both of these tasks, allowing you to compare multiple models, or parameter values in a single run.
To train multiple models in one experiment, the training and test datasets can be reused by directing the datasets to multiple training branches as follows:
The preceding experiment is similar to the earlier training experiment, except that there are two Train Model modules with different algorithms as inputs. The results of the Score Model module are also directed ...
