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

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