Causal Cognition and Spam Classifier

摘要

Previous studies have shown that some combo of human cognitive biases is effective in machine learning. The well-used model of the biases is called loosely symmetric (LS) model. We show the efficiency and accuracy of our loosely symmetric model and its implementation of two cognitive biases, symmetry and mutual exclusively. In this study, we use loosely symmetric as a binary classifier to enhance its accuracy in small datasets.