Classifying Big Data over Networks Via the Logistic Network Lasso

Abstract

We apply network Lasso to solve binary classification and clustering problems on network structured data. In particular we generalize ordinary logistic regression to non-Euclidean data defined over a complex network structure. The resulting logistic network Lasso classifier amounts to solving a convex optimization problem. A scalable classification algorithm is obtained by applying the alternating direction methods of multipliers.