In this paper, we consider the identification of systems based on binary measurements of the output. The linear part of the system is parameterized by a Finite Impulse Response filter and the binary sensor is parameterized by a threshold. The idea is to formulate the identification problem as a classification problem. This formulation allows the use of supervised learning algorithm such as Support Vector Machines (SVM). Simulation examples are given to illustrate the performance of the presented method.