MACHINE LEARNING DEVICE AND MACHINE LEARNING METHOD

• Main Authors: OKUBO YUSUKE, HASUIKE MASAHARU
• Format: Patent
• Language: Chinese; English
• Published: 15.09.2020
• Subjects: AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING; PERFORMING OPERATIONS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDEDFOR; SHAPING OR JOINING OF PLASTICS; TRANSPORTING; WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE, IN GENERAL

The invention provides a machine learning device and a machine learning method, which can reliably select suitable explanatory variable from specified objective variable and a plurality of explanatoryvariable candidates from a learning model. The machine learning device (200) includes a plurality of sparse modeling processing units (213) and a selection unit (215). The sparse modeling processingunit acquires individual importance degrees for each of explanatory variable candidates, the individual importance degrees being acquired by using respective sparse modeling methods different from each other, each of the sparse modeling methods taking input data including a specified objective variable in a learning model used for industrial activity and the explanatory variable candidates that are candidates for an explanatory variable for explaining the specified objective variable. The selection unit calculates a comprehensive importance degree for each of the explanatory variable candidates based on the individual