This component restores seasonality (1st and 2nd) and trend into the forecasted residual series. The trend model, the seasonal co…

Restore trend into time series forecasts. The trend model has been obtained from the training data based on the row index.

This component restores seasonality into forecasted time series based on the seasonality column that has been extracted from the …

This component provides three different ways for calculating and visualizing the ARR: 1. calculating the total ARR in each month …

This node performs threshold analysis for binary classification or retrieval results with confidence values. It allows to calcula…

This component outputs an interactive dashboard that provides a detailed analysis of airline dataset in terms of Overview, Explor…

Trains a Seasonal AutoRegressive Integrated Moving Average (SARIMA) model. SARIMA models capture temporal structures in time seri…

The Component uses IDs from several data sources to create an interactive pathway analysis based on the web service of Reactome. …

This Component is able to create a Local Interpretable Model-agnostic Explanation (LIME) to explain the predictions of any machin…

Trains an AutoRegressive Integrated Moving Average (ARIMA) model. ARIMA model captures temporal structures in time series data in…

Trains AutoRegressive Integrated Moving Average (ARIMA) models and returns the best model according to the search criterion (AIC,…

This component visualizes how different error metrics change as a forecast horizon grows. Use this component to better understand…

This component shows the (cumulative) ARR or MRR by time and time-based cohort. Cohorts are used to group individual records by t…

Computes predictions from an estimated AutoRegressive Integrated Moving Average (ARIMA) model. Two types of predictions are compu…

Computes predictions from an estimated Seasonal AutoRegressive Integrated Moving Average (SARIMA) model. Two types of predictions…

This component checks whether the selected timestamp column is uniformly sampled in the selected time scale. Missing values will …

This component shows the (cumulative) customer count or churn rate by time and time-based cohort. Cohorts are used to group indiv…

This is an implementation of the model explanation technique developed by H2O.ai called K-LIME using the KNIME H2O Machine Learni…