Fast classification using sparse decision DAGs

06/27/2012
by   Djalel Benbouzid, et al.
0

In this paper we propose an algorithm that builds sparse decision DAGs (directed acyclic graphs) from a list of base classifiers provided by an external learning method such as AdaBoost. The basic idea is to cast the DAG design task as a Markov decision process. Each instance can decide to use or to skip each base classifier, based on the current state of the classifier being built. The result is a sparse decision DAG where the base classifiers are selected in a data-dependent way. The method has a single hyperparameter with a clear semantics of controlling the accuracy/speed trade-off. The algorithm is competitive with state-of-the-art cascade detectors on three object-detection benchmarks, and it clearly outperforms them when there is a small number of base classifiers. Unlike cascades, it is also readily applicable for multi-class classification. Using the multi-class setup, we show on a benchmark web page ranking data set that we can significantly improve the decision speed without harming the performance of the ranker.

READ FULL TEXT

Authors

page 6

09/11/2013

Enhancements of Multi-class Support Vector Machine Construction from Binary Learners using Generalization Performance

We propose several novel methods for enhancing the multi-class SVMs by a...
02/05/2018

Enhancing Multi-Class Classification of Random Forest using Random Vector Functional Neural Network and Oblique Decision Surfaces

Both neural networks and decision trees are popular machine learning met...
04/01/2022

Building Decision Forest via Deep Reinforcement Learning

Ensemble learning methods whose base classifier is a decision tree usual...
10/23/2018

DCSVM: Fast Multi-class Classification using Support Vector Machines

We present DCSVM, an efficient algorithm for multi-class classification ...
10/02/2020

An ensemble of Density based Geometric One-Class Classifier and Genetic Algorithm

One of the most rising issues in recent machine learning research is One...
09/30/2021

Learning the Markov Decision Process in the Sparse Gaussian Elimination

We propose a learning-based approach for the sparse Gaussian Elimination...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.