Probabilistic Decision Trees using SVM for Multi-class Classification
TypeCommunications avec actes
In the automotive repairing backdrop, retrieving from previously solved incident the database features that could support and speed up the diagnostic is of great usefulness. This decision helping process should give a fixed number of the more relevant diagnostic classified in a likelihood sense. It is a probabilistic multi-class classification problem. This paper describes an original classification technique, the Probabilistic Decision Tree (PDT) producing a posteriori probabilities in a multi-class context. It is based on a Binary Decision Tree (BDT) with Probabilistic Support Vector Machine classifier (PSVM). At each node of the tree, a bi-class SVM along with a sigmoid function are trained to give a probabilistic classification output. For each branch, the outputs of all the nodes composing the branch are combined to lead to a complete evaluation of the probability when reaching the final leaf (representing the class associated to the branch). To illustrate the effectiveness of PDTs, they are tested on benchmark datasets and results are compared with other existing approaches.
Showing items related by title, author, creator and subject.
MECHBAL, Nazih; URIBE, Juan Sebastian; REBILLAT, Marc (Elsevier, 2015)In this paper, a probabilistic multi-class pattern recognition algorithm is developed for damage detection, localization, and quantification in smart mechanical structures. As these structures can face damages of different ...
BARTHES, Clément; MECHBAL, Nazih; MOSALAM, Khalid; REBILLAT, Marc (2017)The ability to monitor the health of complex structures such as aeronautic or civil engineering structures in real time is becoming increasingly important. This process is referred to as structural health monitoring (SHM) ...
BAKIR, Myriam; REBILLAT, Marc; MECHBAL, Nazih (IFAC, 2015)Structural damages result in nonlinear dynamical signatures that significantly help for their monitoring. A damage type classification approach is proposed here that is based on a parallel Hammerstein models ...
FENDZI, Claude; REBILLAT, Marc; MECHBAL, Nazih; GUSKOV, Mikhail; COFFIGNAL, Gérard (SAGE Journals, 2016)This paper presents a temperature compensation method for Lamb wave structural health monitoring. The proposed approach considers a representation of the piezo-sensor signal through its Hilbert transform that allows one ...
GHRIB, Meriem; BERTHE, Laurent; MECHBAL, Nazih; REBILLAT, Marc; GUSKOV, Mikhail; ECAULT, Romain; BEDREDDINE, Nas (Elsevier, 2017)Structural Health Monitoring (SHM) is defined as the process of implementing a damage identification strategy for aerospace, civil and mechanical engineering infrastructures. SHM can be organized into five main steps: ...