Revisit of Logistic Regression
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2013, Vol 4, Issue 5
Abstract
Logistic regression (LR) is widely applied as a powerful classification method in various fields, and a variety of optimization methods have been developed. To cope with large-scale problems, an efficient optimization method for LR is required in terms of computational cost and memory usage. In this paper, we propose an efficient optimization method using non-linear conjugate gradient (CG) descent. In each CG iteration, the proposed method employs the optimized step size without exhaustive line search, which significantly reduces the number of iterations, making the whole optimization process fast. In addition, on the basis of such CG-based optimization scheme, a novel optimization method for kernel logistic regression (KLR) is proposed. Unlike the ordinary KLR methods, the proposed method optimizes the kernel-based classifier, which is naturally formulated as the linear combination of sample kernel functions, directly in the reproducing kernel Hilbert space (RKHS), not the linear coefficients. Subsequently, we also propose the multiple-kernel logistic regression (MKLR) along with the optimization of KLR. The MKLR effectively combines the multiple types of kernels with optimizing the weights for the kernels in the framework of the logistic regression. These proposed methods are all based on CG-based optimization and matrix-matrix computation which is easily parallelized such as by using multi-thread programming. In the experimental results on multi-class classifications using various datasets, the proposed methods exhibit favorable performances in terms of classification accuracies and computation times.
Authors and Affiliations
Takumi Kobayashi, Kenji Watanabe, Nobuyuki Otsu
Keywords
Related Articles
- EP ID EP87475
- DOI 10.14569/IJACSA.2013.040519
- Views 61
- Downloads 0
Design and Simulation of a Low-Voltage Low-Offset Operational Amplifier
In many applications, offset of the OP-AMPs should be canceled to high accuracy be accomplished. In this work, an asymmetrical differential input circuit with active DC offset rejection circuit was implemented to minimiz...
Scrum Method Implementation in a Software Development Project Management
To maximize the performance, companies conduct a variety of ways to increase the business profit. The work management between one company and the other company is different, so the differences in the management may cause...
A Model for Forecasting the Number of Cases and Distribution Pattern of Dengue Hemorrhagic Fever in Indonesia
Dengue Hemorrhagic Fever (DHF) ourbreaks is one of the lethal health problems in Indonesia. Aedes aegypti type of insect prolefiration as the main vector of DHF has affected climate factors, such as temperature, humidity...
Evaluating the Applicability of a Social Content Management Framework: A Case Analysis
Social media platform plays an important role in engaging customers. The social content resulting from social media interactions between the organisations and the customers need a proper management. Therefore, in this wo...
Design and Modeling of RF Power Amplifiers with Radial Basis Function Artificial Neural Networks
A radial basis function (RBF) artificial neural network model for a designed high efficiency radio frequency class-F power amplifier (PA) is presented in this paper. The presented amplifier is designed at 1.8 GHz operati...