DISTRIBUTED MACHINE LEARNING USING SHARED CONFIDENCE VALUES

An embodiment includes generating, by a first edge computing device having a sensor, a dataset based on sensor data from the sensor. The embodiment generates, by an analytics engine hosted by the first edge computing device, a classification dataset comprising a classification for the dataset and a confidence value associated with the classification. The embodiment calculates a confidence difference between the confidence value and a reference confidence value received with a reference classification from a second edge computing device. The embodiment compares the confidence difference to a difference threshold value and generates, in a case in which the confidence difference is greater than the difference threshold value, a replacement dataset as an output replacement for the classification dataset, where the replacement dataset comprises the reference classification and an indication that the confidence value is less than the reference confidence value.