Automatic recognition of data entry errors (wrong type values)
Automatic and manual column type identification (numeric, categorical, date, time, text)
Automatic random dataset division onto training, validation and test sets
Detailed Data Analysis Report
For experienced users
Manual dataset division onto training, validation and test sets (random or sequential)
Visual representation of data anomalies in Data Analysis Details window
Ability to accept/ignore rows and columns manually
Manual min/max values specification to anticipate bigger values in future data for forecasting
Detailed Preprocessing Report
Design Suitable Neural Network
Fully automated neural network design - automatically search for the best architecture and train the most suitable neural network to solve your problem
Three timesaving methods of neural network architecture search
Exhaustive architecture search with customizable parameters
Genetic algorithms architecture search with customizable parameters
Automatic training algorithm selection
For experienced users
Manual selection of training algorithms: Conjugate Gradient Descent, Levenberg-Marquardt, Quick-Propagation, Incremental and Batch Back-Propagation