Enhanced robust univariate classification methods for solving outliers and overfitting problems
The robustness of some classical univariate classifiers is hampered if the data are
contaminated. Overfitting is another hiccup when the data sets are uncontaminated with a …
contaminated. Overfitting is another hiccup when the data sets are uncontaminated with a …
Examining the trend of literature on classification modelling: a bibliometric approach
This paper analyses and reports various types of published works related to classification or
discriminant modelling. This paper adopted a bibliometric analysis based on the data …
discriminant modelling. This paper adopted a bibliometric analysis based on the data …
[PDF][PDF] Classification of Familial Hypercholesterolaemia Using Ordinal Logistic Regression.
Familial hypercholesterolaemia (FH) is a genetic disease that causes the elevation of
lowdensity lipoprotein cholesterol (LDL-C), which subsequently leads to premature coronary …
lowdensity lipoprotein cholesterol (LDL-C), which subsequently leads to premature coronary …
[PDF][PDF] Developing a New Estimation Approach for Constructing a Flexible Location Model to Address Challenges with Numerous Empty and Non-Empty Cells
This paper aims to address the challenges posed by the simultaneous occurrence of
numerous empty and many non-empty cells in the Location Model (LM). The LM is a …
numerous empty and many non-empty cells in the Location Model (LM). The LM is a …
Systematic Literature Review of Mixed Variables Classification
P Ngu, H Hamid - International Journal of Data Science and Advanced …, 2023 - ijdsaa.com
Classification is one of the most popular approaches that had been used in a variety of
fields. There are a lot of classification methods that are applicable to classify objects into …
fields. There are a lot of classification methods that are applicable to classify objects into …
Performance Analysis and Discrimination Procedure of Two-Group Location Model with Some Continuous and High-Dimensional of Binary Variables
This research's primary goal was to evaluate the performance analysis of the recently
constructed smoothed location models (SLMs) for discrimination purposes by combining two …
constructed smoothed location models (SLMs) for discrimination purposes by combining two …
Adaptive Variable Extractions with LDA for Classification of Mixed Variables, and Applications to Medical Data
The strategy surrounding the extraction of a number of mixed variables is examined in this
paper in building a model for Linear Discriminant Analysis (LDA). Two methods for …
paper in building a model for Linear Discriminant Analysis (LDA). Two methods for …