What is the main function of the TS Data Preparation Node?

The main function of the TS Data Preparation Node is to handle time series data cleaning, summarization, and transformation. This node is specifically designed to prepare time series data for modeling and analysis by addressing various preprocessing tasks that are essential in time series analysis. It can assist in managing missing values, smoothing data, and converting data into a suitable format for effective modeling.

By focusing on data cleaning, the node ensures that the dataset is free of anomalies and inconsistencies that could negatively impact subsequent analyses. Summarization allows for handling large datasets by condensing them into more manageable forms, making it easier to identify patterns or trends over time. Transformation may include aggregating data over specified time intervals or reformatting the series to meet the requirements of specific forecasting techniques.

While the other options mention important aspects of time series analysis, they are not the primary functions of the TS Data Preparation Node. Creating seasonal decomposition, generating forecasts, and computing similarity measures typically fall within the realm of other nodes or processes in time series analysis rather than the preparation phase, which is where this node excels.