Abstract: To automate time series forecasting machine learning pipeline generation, a data allocation size of time series data may be determined based on one or more characteristics of a time series data set. The time series data may be allocated for use by candidate machine learning pipelines based on the data allocation size. Features for the time series data may be determined and cached by the candidate machine learning pipelines. Predictions of each of the candidate machine learning pipelines using at least the one or more features may be evaluated. A ranked list of machine learning pipelines may be automatically generated from the candidate machine learning pipelines for time series forecasting based upon evaluating predictions of each of the one or more candidate machine learning pipelines.

Abstract: The interactive data retrieval system utilizes a computer system that has a telephone interface, a memory, and a facsimile transmission device. The telephone interface is connected to a telephone line and receives information request signals from the caller and transmits audio responses over the telephone line to that person based upon the requested signals. The computer program converts the information request signals into a search request command. The program searches the data compilation and obtains a data set based upon that command. The data set may be an acknowledgment of the subscriber or customer account number and security code or, on a broader level, may be the number of hits or records present in the data set that was generated by the search of the data compilation. The program produces signals which represent audio response signals and the audio response signals are sent via the telephone interface to the subscriber or customer.