«ensemble learning techniques»
۲۸۸۲ نتیجهThe Use of the Ambiguity Decomposition in Neural Network Ensemble Learning Methods
We analyze the formal grounding behind Negative Correlation (NC) Learning, an ensemble learning technique developed in the evolutionary computation literature. We show that by removing an assumption made in the original work, NC can be seen to be exploiting the well-known Ambigui
Energy Consumption Prediction Using Data Reduction and Ensemble Learning Techniques
Building energy problems have various kinds of aspects, one which is the difficulty measuring efficiency. With current data development, efficiency measurements can be made by developing predictive models to estimate future building needs. However, with massive amount data, sever
Label Ranking with Partial Abstention using Ensemble Learning
In label ranking, the problem is to learn a mapping from instances to rankings over a finite set of predefined class labels. In this paper, we consider a generalization of this problem, namely label ranking with a reject option. Just like in conventional classification, where a c
Ensemble Learning for Low-Level Hardware-Supported Malware Detection
Recent work demonstrated hardware-based online malware detection using only low-level features. This detector is envisioned as a first line of defense that prioritizes the application of more expensive and more accurate software detectors. Critical to such a framework is the dete
A Novel Fault Detection and Classification Strategy for Photovoltaic Distribution Network Using Improved Hilbert–Huang Transform and Ensemble Learning Technique
Due to the increased integration of distributed generations in networks, their development and operation are facing protection challenges that traditional systems incapable addressing. These problems include variations fault current during various modes, diverse network topology,
Using Incremental Ensemble Learning Techniques to Design Portable Intrusion Detection for Computationally Constraint Systems
Computers have evolved over the years, and as evolution continues, we been ushered into an era where high-speed internet has made it possible for devices in our homes, hospital, energy, industry to communicate with each other. This is known Internet of Things (IoT). IoT several b
Construction of a Frequency Compliant Unit Commitment Framework Using an Ensemble Learning Technique
Frequency control is essential to ensure reliability and quality of power systems. North American Electric Reliability Corporation’s (NERC) Control Performance Standard 1 (CPS1) widely adopted by many operating authorities examine the frequency control. The authority would have a
Bankruptcy Prediction by Supervised Machine Learning Techniques : A Comparative Study
It is very important for financial institutions which are capable of accurately predicting business failure. In literature, numbers of bankruptcy prediction models have been developed based on statistical and machine learning techniques. In particular, many machine learning techn
A comparative assessment of the performance of ensemble learning in customer churn prediction
Customer churn is a main concern of most firms in all industries. The aim of customer churn prediction is detecting customers with high tendency to leave a company. Although, many modeling techniques have been used in the field of churn prediction, performance of ensemble methods
A compressed sensing approach for efficient ensemble learning
This paper presents a method for improved ensemble learning, by treating the optimization of an ensemble of classifiers as a compressed sensing problem. Ensemble learning methods improve the performance of a learned predictor by integrating a weighted combination of multiple pred