CPC G06F 18/24765 (2023.01) [G06F 16/285 (2019.01); G06F 18/2148 (2023.01); G06F 18/40 (2023.01); G06N 5/025 (2013.01); G06N 20/00 (2019.01)] | 20 Claims |
1. A machine learning apparatus comprising:
a first data storage device including a first distributed data set;
a first network connector connected to a network, the first network connector in communications with a second network connector on a second data storage device on a machine learning server, the second data storage device including a second distributed data set;
a model orchestrator, stored in the first data storage device and executing on the machine learning apparatus, the model orchestrator programmed to publish a set of data identifiers including data elements and data features, and programmed to send the set of the data identifiers through the first network connector to the second network connector to a second prediction manager executing on the machine learning server;
a first prediction manager connected to the first data storage device programmed to receive the set of the data identifiers from the model orchestrator and to calculate a first quality control metric and a first rule set using a first machine learning algorithm on the first distributed data set;
a prediction orchestrator programmed to receive the first quality control metric and the first rule set from the first prediction manager and to receive from the second prediction manager a second quality control metric and a second rule set determined from the second distributed data set; and
the prediction orchestrator further programmed to combine the first rule set and the second rule set into a common rule set and to combine the first quality control metric and the second quality control metric into a combined quality control metric.
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