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Factor Analysis, Statistical

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Comparison of Seven Methods for Boolean Factor Analysis and Their Evaluation by Information Gain.

IEEE transactions on neural networks and learning systems
An usual task in large data set analysis is searching for an appropriate data representation in a space of fewer dimensions. One of the most efficient methods to solve this task is factor analysis. In this paper, we compare seven methods for Boolean ...

Advanced Residuals Analysis for Determining the Number of PARAFAC Components in Dissolved Organic Matter.

Applied spectroscopy
Parallel factor analysis (PARAFAC) has facilitated an explosion in research connecting the fluorescence properties of dissolved organic matter (DOM) to its functions and biogeochemical cycling in natural and engineered systems. However, the validatio...

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

Computational intelligence and neuroscience
Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collec...

Advanced analytical methodologies for measuring healthy ageing and its determinants, using factor analysis and machine learning techniques: the ATHLOS project.

Scientific reports
A most challenging task for scientists that are involved in the study of ageing is the development of a measure to quantify health status across populations and over time. In the present study, a Bayesian multilevel Item Response Theory approach is u...

The neuromorphological caudate-putaminal clustering of neostriate interneurons: Kohonen self-organizing maps and supervised artificial neural networks with multivariate analysis.

Journal of theoretical biology
AIMS: The objective of this study is to investigate the possibility of the neuromorphotopological clustering of neostriate interneurons (NSIN) and their consequent classification into caudate (CIN) and putaminal neuron type (PIN), according to the nu...

Using Neural Networks to predict HFACS unsafe acts from the pre-conditions of unsafe acts.

Ergonomics
Human Factors Analysis and Classification System (HFACS) is based upon Reason's organizational model of human error which suggests that there is a 'one to many' mapping of condition tokens (HFACS level 2 psychological precursors) to unsafe act tokens...