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Factor Analysis in Education Research Using R
Factor analysis is a method commonly employed to reduce a large number of variables into fewer numbers of factors. The method is often used to...
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Latent Factor Analysis for High-dimensional and Sparse Matrices A particle swarm optimization-based approach
Latent factor analysis models are an effective type of machine learning model for addressing high-dimensional and sparse matrices, which are...
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A Comparative Investigation on Model Selection in Binary Factor Analysis
Binary factor analysis has been widely used in data analysis with various applications. Most studies assume a known hidden factors number k or...
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Factor Analysis and Probabilistic Principal Component Analysis
Learning models can be divided into discriminative and generative models. Discriminative models discriminate the classes of data for better...
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An empirical analysis of software fault proneness using factor analysis with regression
The fault prediction process becomes essential in the early stages of Software Development Life Cycle, so as to be able to generate various modules...
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Framework Proposal for Strategic Factor Analysis Driven by Design
This work proposes a new framework for business strategic analysis in scenarios of uncertainty and change. To facilitate a reorganization and update...
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Evaluation Method of Skilled Personnel Based on Factor Analysis and BP Neural Network
Skilled talents are the core of any organization; They are the people who make or break the company. A successful enterprise depends on the skills...
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Factor Analysis of Purchasing a Third-Category Beer
There is a beer known as the third beer in Japan. This beer has been sold at a lower price than others due to the difference in tax rates. Taking...
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Basic values in artificial intelligence: comparative factor analysis in Estonia, Germany, and Sweden
Increasing attention is paid to ethical issues and values when designing and deploying artificial intelligence (AI). However, we do not know how...
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Two-Stage Deep Ensemble Paradigm Based on Optimal Multi-scale Decomposition and Multi-factor Analysis for Stock Price Prediction
Stock price forecasting is important for financial risk management and investment decisions. However, traditional forecasting techniques are...
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A Dynamic Linear Bias Incorporation Scheme for Nonnegative Latent Factor Analysis
High-Dimensional and Incomplete (HDI) data is commonly encountered in big data-related applications like social network services systems, which are...
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Factor Space: Cognitive Computation and Systems for Generalized Genes
The purpose is to generalize and expand the vector space to factor analysis, and then simplify the knowledge graph to the factor graph, focusing on...
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An efficient annealing-assisted differential evolution for multi-parameter adaptive latent factor analysis
A high-dimensional and incomplete (HDI) matrix is a typical representation of big data. However, advanced HDI data analysis models tend to have many...
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Loss Filtering Factor for Crowd Counting
In crowd counting datasets, each person is annotated by a point, typically representing the center of the head. However, due to the dense crowd,...
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DRL-HIFA: a dynamic recommendation system with deep reinforcement learning based Hidden Markov Weight Updation and factor analysis
Recommendation Systems have obtained huge attention with notion to assist users in determining their interests by prognosticating their ratings or...
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Trust factor-based analysis of user behavior using sequential pattern mining for detecting intrusive transactions in databases
Organizations today are employing databases on a large scale to store data essential for their functioning. Malicious access and modifications of the...
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A novel factor analysis-based metric learning method for kinship verification
This paper presents a novel factor analysis-based metric learning (FAML) method for kinship verification. While metric learning has achieved...
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Surrogate Models for the Compressibility Factor of Natural Gas
The paper presents an example of the so-called surrogate modeling. This is a computer modeling technique where machine learning methods are used to...
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An Exploratory Factor Analysis of Personality Factors: An Insider Threat Perspective
This study used an exploratory factor analysis to examine the factors underlying personality traits that influence the constructs of information...
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Introducing a bibliometric index based on factor analysis
This work applies a factor analysis with VARIMAX rotation to develop a bibliometric indicator, named the Weighted Factor Index, in order to derive a...