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Full-Text Articles in Engineering

Optimizing Ensemble Weights For Machine Learning Models: A Case Study For Housing Price Prediction, Mohsen Shahhosseini, Guiping Hu, Hieu Pham Jul 2019

Optimizing Ensemble Weights For Machine Learning Models: A Case Study For Housing Price Prediction, Mohsen Shahhosseini, Guiping Hu, Hieu Pham

Guiping Hu

Designing ensemble learners has been recognized as one of the significant trends in the field of data knowledge especially in data science competitions. Building models that are able to outperform all individual models in terms of bias, which is the error due to the difference in the average model predictions and actual values, and variance, which is the variability of model predictions, has been the main goal of the studies in this area. An optimization model has been proposed in this paper to design ensembles that try to minimize bias and variance of predictions. Focusing on service sciences, two well-known ...


Optimizing Ensemble Weights For Machine Learning Models: A Case Study For Housing Price Prediction, Mohsen Shahhosseini, Guiping Hu, Hieu Pham Jul 2019

Optimizing Ensemble Weights For Machine Learning Models: A Case Study For Housing Price Prediction, Mohsen Shahhosseini, Guiping Hu, Hieu Pham

Mohsen Shahhosseini

Designing ensemble learners has been recognized as one of the significant trends in the field of data knowledge especially in data science competitions. Building models that are able to outperform all individual models in terms of bias, which is the error due to the difference in the average model predictions and actual values, and variance, which is the variability of model predictions, has been the main goal of the studies in this area. An optimization model has been proposed in this paper to design ensembles that try to minimize bias and variance of predictions. Focusing on service sciences, two well-known ...


Determination Of Rule Patterns In Complex Event Processing Using Machine Learning Techniques, Nijat Mehdiyev, Julian Krumeich, David Lee Enke, Dirk Werth, Peter Loos Mar 2019

Determination Of Rule Patterns In Complex Event Processing Using Machine Learning Techniques, Nijat Mehdiyev, Julian Krumeich, David Lee Enke, Dirk Werth, Peter Loos

David Lee Enke

Complex Event Processing (CEP) is a novel and promising methodology that enables the real-time analysis of stream event data. The main purpose of CEP is detection of the complex event patterns from the atomic and semantically low-level events such as sensor, log, or RFID data. Determination of the rule patterns for matching these simple events based on the temporal, semantic, or spatial correlations is the central task of CEP systems. In the current design of the CEP systems, experts provide event rule patterns. Having reached maturity, the Big Data Systems and Internet of Things (IoT) technology require the implementation of ...


Optimization Algorithms For Machine Learning Problems, Hiva Ghanbari Jan 2019

Optimization Algorithms For Machine Learning Problems, Hiva Ghanbari

Theses and Dissertations

In the first chapter of this thesis, we analyze the global convergence rate of a proximal quasi-Newton algorithm for solving composite optimization problems, in both exact and inexact settings, in the case when the objective function is strongly convex. W


Optimizing Ensemble Weights For Machine Learning Models: A Case Study For Housing Price Prediction, Mohsen Shahhosseini, Guiping Hu, Hieu Pham Jan 2019

Optimizing Ensemble Weights For Machine Learning Models: A Case Study For Housing Price Prediction, Mohsen Shahhosseini, Guiping Hu, Hieu Pham

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

Designing ensemble learners has been recognized as one of the significant trends in the field of data knowledge especially in data science competitions. Building models that are able to outperform all individual models in terms of bias, which is the error due to the difference in the average model predictions and actual values, and variance, which is the variability of model predictions, has been the main goal of the studies in this area. An optimization model has been proposed in this paper to design ensembles that try to minimize bias and variance of predictions. Focusing on service sciences, two well-known ...