Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 14 of 14 for “"FEATURES SELECTION"”.
-
A FEATURES EXTRACTION WRAPPER METHOD FOR NEURAL NETWORKS WITH APPLICATION TO DATA MINING AND MACHINE LEARNING
This dissertation presents a novel features selection wrapper method based on neural networks, named the Binary Wrapper for Features Selection Technique. The major aim of this method is to reduce the computation time that is consumed during the implementation of the process of features selection …
-
Predicting an Economic Recession Using Machine Learning Techniques
… for addressing imbalance data with suitable features selection strategy to enhance the performance of the machine learning algorithm developed. Furthermore, artificial neural network(ANN) and Random Forest (RF) were used in predicting economic recession using ML techniques. This study would …
-
Parameter reduction in deep learning and classification
… of our work focuses on using dominancy between features in the aim to select a relevant subset of informative features. We propose 3 variations, with different benefits, including fast filter features selection and a hybrid filter-wrapper approach. In the second section, dedicated to deep …
-
A new feature engineering framework for financial cyber fraud detection using machine learning and deep learning
… framework that can produce the most effective features set for any ML and DL algorithms by taking both methods of feature engineering and features selection into a new framework. The framework consists of two main components: feature creation and feature selection. The purpose of feature …
-
Machine Learning Approaches and Web-Based System to the Application of Disease Modifying Therapy for Sickle Cell
… with missing values, multi-class datasets, and features selection. For the classification and discriminant analysis of SCD datasets, 7 classifiers based on machine learning models are selected representing linear and non-linear methods. After running these classifiers with a single model, the …
-
Lightweight intrusion detection of attacks on the Internet of Things (IoT) in critical infrastructures.
… devices. This study proposes an Optimized Common Features Selection and Deep Autoencoder (OCFSDA) technique for lightweight intrusion detection, which is computationally efficient and cost-effective for the IoT. The OCFSDA was achieved by leveraging Shallow Deep Learning to develop a lightweight …
-
Tools for Autonomous Process Control
… for initialization, assessment of basic process features, selection and tuning of on-line controller, monitoring of the on-line control performance, and fault diagnosis. Implementation aspects and software architectures of an autonomous single loop controller are also discussed. In particular, …
-
Deep Learning for Human MicroRNA Precursor Prediction: A Systematic Literature Review
… studies indicated that the use of few input features and a lack of domain understanding of selected input features could impact the accuracy of the results, causing significant bias and making the models appear to be a 'black box.' This study aims to gain more insight into the features …
-
Enhanced flare prediction by advanced feature extraction from solar images : developing automated imaging and machine learning techniques for processing solar images and extracting features from active regions to enable the efficient prediction of solar flares.
… image processing, machine learning, and feature selection algorithms, with advances in solar physics in order to extract valuable knowledge from historical solar data, related to active regions and flares. The aim of this thesis is to achieve the followings: i) The design of a new measurement, …
-
Enhanced flare prediction by advanced feature extraction from solar images : developing automated imaging and machine learning techniques for processing solar images and extracting features from active regions to enable the efficient prediction of solar flares
… image processing, machine learning, and feature selection algorithms, with advances in solar physics in order to extract valuable knowledge from historical solar data, related to active regions and flares. The aim of this thesis is to achieve the followings: i) The design of a new measurement, …
-
Knowledge Acquisition from User Reviews for Interactive Question Answering
… can be confused by the need to consider many features before they can reach a decision. Interactive question answering (IQA) systems can help customers in this process, by answering questions about products and initiating a dialogue with the customers when their needs are not clearly defined. …
-
An Artificial Intelligence Approach to Concatenative Sound Synthesis
… Thus, for the rest of the study, only features that represent the timbral information were included, as musicians are the target user for the findings of this study. Another issue with the current state of CSS systems is the user control flexibility, in particular during segment …
-
Digital Image Processing via Combination of Low-Level and High-Level Approaches.
… the performance. In Hand Gesture Recognition, 3 features of every testing image are input to Gaussian Mixture Model (GMM), and then the Expectation Maximization algorithm (EM)is used to compare the GMM from testing images and GMM from training images in order to classify the results. In Medical …
-
Multi-Platform Molecular Data Integration and Disease Outcome Analysis
… to both biologically and statistically boost the features selection process for proper detection of the true predictive players of survival. The first approach is data-driven yet biologically informed. Consistent with the biological hierarchy from DNA to RNA, we prioritize each survival-relevant …