Automate the end-to-end process of feature engineering and selection by using in-built capabilities. Make use of AutoML to achieve the best possible model performance and improve it further with automated hyperparameter tuning. Leverage the one-click option to deploy the model once it’s developed and evaluated
Automated Data Science Capabilities of NewgenONE Platform
Automated Feature Engineering
Create various features automatically from different datasets by analyzing the relationship between columns and tables
Generate new features with the automated handling of the depth of the relationship between datasets
Add custom rules while creating new features
Automated Feature Selection
Achieve better model performance using ML-based feature selection from thousands of features to choose from
Get automated feature validation options based on the type of modeling algorithm
High-performance Auto ML
Get the best-suited model performance, with ML auto-selecting ideal pre-processing modeling algorithms and parameter configuration
Improve model performance with automated hyper parameter tuning through several optimization techniques, such as grid search, Bayesian optimization, etc.
Optimize the computation costs by using time-bound auto ML capabilities
Automated Model Deployment and Retraining
Ensure one-click deployment once the model is developed and evaluated
Leverage auto model retraining and selection based on a predefined frequency or an event