Parallel learning-A new framework for machine learning

In this paper, we propose a new framework of machine learning theory, parallel learning, which incorporates and inherits many elements from various existing machine learning theories. Special designs are also presented to deal with some important problems in the machine learning research field, e.g., useful data retrieval from big data using software defined artificial systems, combination of predictive learning and ensemble learning, application of Merton's law to prescriptive learning.