The Hybrid Intelligent Information System for Music Classification

The article proposes an approach for music classification problem using hybrid intelligent information systems (HIIS). The HIIS consists of two main components: the subconsciousness module and the consciousness module. The subconsciousness module is implemented as a set of binary classifiers based on the LSTM network. The output of the subconsciousness module is the metadata stored in the metadata buffer. The consciousness module is implemented using decision trees approach. The implementation is based on the CART algorithm from the scikit-learn library. The output of the consciousness module is the predicted class of the music classification problem. The experiments were conducted using custom dataset. The algorithms of three levels of complexity were used for experiments: the logistic regression approach (the simplest model), the multilayer perceptron approach (the model of medium complexity), the HIIS approach (the model of high complexity). The results of the experiments make sure the validity of the proposed HIIS approach.