Task type & Metric
Select the task type: Regression / Binary Classification / Multiclass Classification and the metric to measure model quality. Neuton can automatically detect a task type based on the target variable values, but you can also specify this parameter manually.
For Binary and Multiclass classification task types, the default value of the target metric is Accuracy, for the Regression task type the default target metric is RMSE (Root mean squared error, for more information please refer to "Metrics definition").
During the training phase, the platform will measure the validation metric at each training iteration using a 10-fold cross-validation approach. Neuton has a built-in patented feature to prevent overfitting (overtraining) which stops training right before overfitting starts to occur. If the holdout validation dataset was specified final metrics will be calculated for it.
Regardless of the target metric you have chosen, the platform will count all the metrics available on the platform for this type of task. Detailed metrics descriptions are available in the Glossary.