A Bi-objective Hyper-Heuristic Support Vector Machines for Big Data Cyber-Security

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Bayesian Nonlinear Support Vector Machines for Big Data

We propose a fast inference method for Bayesian nonlinear support vector machines that leverages stochastic variational inference and inducing points. Our experiments show that the proposed method is faster than competing Bayesian approaches and scales easily to millions of data points. It provides additional features over frequentist competitors such as accurate predictive uncertainty estimate...

متن کامل

A nested heuristic for parameter tuning in Support Vector Machines

The default approach for tuning the parameters of a Support Vector Machine (SVM) is a grid search in the parameter space. Different metaheuristics have been recently proposed as a more efficient alternative, but they have only shown to be useful in models with a low number of parameters. Complex models, involving many parameters, can be seen as extensions of simpler and easy-to-tune models, yie...

متن کامل

An economic analysis for integrated bi-objective biofuel supply chain design using support vector machine

Using second-generation biomass and biofuel deal with environmental pollution and CO2 emissions. Therefore, this paper design an integrated multi-period bi-objective biofuel supply chain network using support vector machine (SVM) and economic analysis to reduce the cost of generating biofuels and CO2 emissions. The economic analysis consists of three scenarios for supplyin...

متن کامل

Multi-Objective Optimization of Support Vector Machines

Designing supervised learning systems is in general a multi-objective optimization problem. It requires finding appropriate trade-offs between several objectives, for example between model complexity and accuracy or sensitivity and specificity. We consider the adaptation of kernel and regularization parameters of support vector machines (SVMs) by means of multi-objective evolutionary optimizati...

متن کامل

Continuous Hyper-parameter Learning for Support Vector Machines

In this paper, we address the problem of determining optimal hyper-parameters for support vector machines (SVMs). The standard way for solving the model selection problem is to use grid search. Grid search constitutes an exhaustive search over a pre-defined discretized set of possible parameter values and evaluating the cross-validation error until the best is found. We developed a bi-level opt...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Access

سال: 2018

ISSN: 2169-3536

DOI: 10.1109/access.2018.2801792