MACHINE LEARNING BASED MODEL FOR SPECTRAL SCAN AND ANALYSIS

摘要

Various aspects of the subject technology relate to methods, systems, and machine-readable media for classifying interfering devices. The method includes collecting data samples from a set of known interfering devices, the data samples having characteristics of the set of known interfering devices. The method also includes compiling known feature vectors corresponding to the characteristics of the set of known interfering devices. The method also includes executing the known feature vectors on machine learning algorithms to train the machine learning algorithms to classify the set of known interfering devices. The method also includes generating a machine learning model based on performances of the machine learning algorithms, the machine learning model including at least one of the machine learning algorithms. The method also includes executing future feature vectors corresponding to a set of future interfering devices on the machine learning model to classify the set of future interfering devices.