The objective of this work is to identify which carcass and cut characteristics have the best discriminatory power, between sexes and slaughter weights, through discriminant analysis. Were used 32 ...
Abstract: Linear discriminant analysis (LDA) is a widely used technique for data classification. The method offers adequate performance in many classification problems, but it becomes inefficient when ...
Learned the fundamentals and applications in ML: Intro to Prob. & Linear algebra, Decision Theory, MLE & BE, Linear Model, Linear Discriminant function, Perceptron, FLD, PCA, Non-parametric Learning, ...
Most freshwater mussels have larvae (glochidia in Unionidae, Margaritiferidae and Hyriidae) that are parasitic on fishes. This study describes and compares the diversity of glochidia among 17 species ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this work, we demonstrate that Linear Discriminant Analysis (LDA) applied to atomic ...
Autism Spectrum Disorder (ASD) is a developmental condition characterized by social and communication differences. Recent research suggests ASD affects 1-in-44 children in the United States. ASD is ...
The problem of classification in situations where the assumption of normality in the data is violated, and there are non-linear clustered structures in the dataset is addressed. A robust nonparametric ...
Some machine learning models belong to either the “generative” or “discriminative” model categories. Yet what is the difference between these two categories of models? What does it mean for a model to ...
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