AIMC Topic: Discriminant Analysis

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Comparison of the prediction accuracy of machine learning algorithms in crosslinguistic vowel classification.

Scientific reports
Machine learning algorithms can be used for the prediction of nonnative sound classification based on crosslinguistic acoustic similarity. To date, very few linguistic studies have compared the classification accuracy of different algorithms. This st...

A Novel Event-Driven Spiking Convolutional Neural Network for Electromyography Pattern Recognition.

IEEE transactions on bio-medical engineering
Electromyography (EMG) pattern recognition is an important technology for prosthesis control and human-computer interaction etc. However, the practical application of EMG pattern recognition is hampered by poor accuracy and robustness due to electrod...

Advancing prostate cancer detection: a comparative analysis of PCLDA-SVM and PCLDA-KNN classifiers for enhanced diagnostic accuracy.

Scientific reports
This investigation aimed to assess the effectiveness of different classification models in diagnosing prostate cancer using a screening dataset obtained from the National Cancer Institute's Cancer Data Access System. The dataset was first reduced usi...

Sex estimation from long bones: a machine learning approach.

International journal of legal medicine
Sex estimation from skeletal remains is one of the crucial issues in forensic anthropology. Long bones can be a valid alternative to skeletal remains for sex estimation when more dimorphic bones are absent or degraded, preventing any estimation from ...

Machine learning-guided REIMS pattern recognition of non-dairy cream, milk fat cream and whipping cream for fraudulence identification.

Food chemistry
The illegal adulteration of non-dairy cream in milk fat cream during the manufacturing process of baked goods has significantly hindered the robust growth of the dairy industry. In this study, a method based on rapid evaporative ionization mass spect...

Spectrochemical analysis of blood combined with chemometric techniques for detecting osteosarcopenia.

Scientific reports
Among several complications related to physiotherapy, osteosarcopenia is one of the most frequent in elderly patients. This condition is limiting and quite harmful to the patient's health by disabling several basic musculoskeletal activities. Current...

Stimulus classification with electrical potential and impedance of living plants: comparing discriminant analysis and deep-learning methods.

Bioinspiration & biomimetics
The physiology of living organisms, such as living plants, is complex and particularly difficult to understand on a macroscopic, organism-holistic level. Among the many options for studying plant physiology, electrical potential and tissue impedance ...

Machine Learning for Prediction, Classification, and Identification of Immobilized Enzymes for Biocatalysis.

Pharmaceutical research
BACKGROUND: Enzyme immobilization is a beneficial component involved in biocatalytic strategies. Understanding and evaluating the enzyme immobilization system plays an important role in the successful development and implementation of the biocatalysi...

Applying Unsupervised Machine Learning Models to Identify Serve Performance Related Indicators in Women's Volleyball.

Research quarterly for exercise and sport
In volleyball, the effect of different factors on serve performance has usually been analyzed with traditional statistical techniques such as logistic regression or discriminant analysis. In this study, two of the main models used in unsupervised ma...

Structural Analysis and Classification of Low-Molecular-Weight Hyaluronic Acid by Near-Infrared Spectroscopy: A Comparison between Traditional Machine Learning and Deep Learning.

Molecules (Basel, Switzerland)
Confusing low-molecular-weight hyaluronic acid (LMWHA) from acid degradation and enzymatic hydrolysis (named LMWHA-A and LMWHA-E, respectively) will lead to health hazards and commercial risks. The purpose of this work is to analyze the structural di...