Analyzing Time Series Data for Sets of Devices Using Machine Learning Techniques

A non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device:

• to process time series data from multiple devices;
• to generate at least one data forecast by applying, in response to a request from at least one user, one or more machine learning techniques to at least a portion of the processed time series data;
• to compute one or more qualifying values attributable to the at least one generated data forecast by providing the at least one generated data forecast and the at least a portion of the processed time series data to a conformal prediction framework;
• and
• to perform one or more automated actions based at least in part on the at least one generated data forecast and the one or more computed qualifying values.

An apparatus comprising:

• at least one processing device comprising a processor coupled to a memory;
• the at least one processing device being configured:
• to process time series data from multiple devices;
• to generate at least one data forecast by applying, in response to a request from at least one user, one or more machine learning techniques to at least a portion of the processed time series data;
• to compute one or more qualifying values attributable to the at least one generated data forecast by providing the at least one generated data forecast and the at least a portion of the processed time series data to a conformal prediction framework;
• and
• to perform one or more automated actions based at least in part on the at least one generated data forecast and the one or more computed qualifying values.