Advance Analytics – Do You know

Outlier threshold configuration

This enhancement enables the users to define the threshold for identifying outliers based on their specific needs and domain knowledge. By setting the threshold on a scale of 1 to 5, users can adjust the sensitivity of the outlier detection algorithm and customize it to their dataset's unique characteristics.

Key benefits:
- The feature provides the data scientists with an ability to set experience-based thresholds to identify and investigate anomalies in their data, providing valuable insights for anomaly detection use cases across various domains.
CatBoost algorithm under classification

The CatBoost algorithm is designed to handle categorical features effectively, it utilizes gradient boosting principles to create a strong ensemble of decision trees, resulting in highly accurate predictions. With its advanced handling of categorical variables, CatBoost minimizes the need for extensive data pre-processing and feature engineering, saving users valuable time and effort.

Key benefits:
- This feature enables the data scientists to achieve higher prediction accuracy and better model performance, on critical use cases such as Customer Churn Prediction and Fraud Detection.
AutoML

This feature enables automatic selection of algorithms and best input variables in order to build the best classification models.

Key benefits:
- The biggest advantage of this feature is that it empower business analysts and subject matter experts to generate models in a guardrail-safe manner that embeds standard data science best practices into the models.
- AutoML feature can help organizations to open up data science to a broader community of users and make AI more mainstream.
- Another big advantage of this feature is that it greatly reduces the time too value i.e. reduces the effort required to develop a AI model.
Multivariate time series forecasting

This enhancement enables the users to use multiple input variables in time series forecasting, this helps in improving the accuracy and reliability of the forecasted values.

Key benefits:
- Forecasting, making predictions about the future, plays a key role in the decision-making process of any company that wants to maintain a successful business.
- Multivariate time series forecasting allows users to take into account the relationships between different variables hence provide more accurate results.