AIMC Topic: Support Vector Machine

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Construction of College Chinese Blended Teaching Mode Based on Decision Tree Classification Model in New Media Context.

Computational intelligence and neuroscience
Based on the context of new media and big data, this article uses the decision tree classification model to construct the college Chinese hybrid teaching mode. In order to verify the accuracy of ID3 algorithm prediction, the comparison of the ID3 alg...

Precision Medicine Approaches with Metabolomics and Artificial Intelligence.

International journal of molecular sciences
Recent technological innovations in the field of mass spectrometry have supported the use of metabolomics analysis for precision medicine. This growth has been allowed also by the application of algorithms to data analysis, including multivariate and...

Identity and Gender Recognition Using a Capacitive Sensing Floor and Neural Networks.

Sensors (Basel, Switzerland)
In recent publications, capacitive sensing floors have been shown to be able to localize individuals in an unobtrusive manner. This paper demonstrates that it might be possible to utilize the walking characteristics extracted from a capacitive floor ...

Objective Supervised Machine Learning-Based Classification and Inference of Biological Neuronal Networks.

Molecules (Basel, Switzerland)
The classification of biological neuron types and networks poses challenges to the full understanding of the human brain's organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal morpholog...

HMM-Based Action Recognition System for Elderly Healthcare by Colorizing Depth Map.

International journal of environmental research and public health
Addressing the problems facing the elderly, whether living independently or in managed care facilities, is considered one of the most important applications for action recognition research. However, existing systems are not ready for automation, or f...

Machine learning for cell type classification from single nucleus RNA sequencing data.

PloS one
With the advent of single cell/nucleus RNA sequencing (sc/snRNA-seq), the field of cell phenotyping is now a data-driven exercise providing statistical evidence to support cell type/state categorization. However, the task of classifying cells into sp...

Marker-Independent Food Identification Enabled by Combing Machine Learning Algorithms with Comprehensive GC × GC/TOF-MS.

Molecules (Basel, Switzerland)
Reliable methods are always greatly desired for the practice of food inspection. Currently, most food inspection techniques are mainly dependent on the identification of special components, which neglect the combination effects of different component...

Impact of Label Noise on the Learning Based Models for a Binary Classification of Physiological Signal.

Sensors (Basel, Switzerland)
Label noise is omnipresent in the annotations process and has an impact on supervised learning algorithms. This work focuses on the impact of label noise on the performance of learning models by examining the effect of random and class-dependent labe...

Automated assessment of balance: A neural network approach based on large-scale balance function data.

Frontiers in public health
Balance impairment (BI) is an important cause of falls in the elderly. However, the existing balance estimation system needs to measure a large number of items to obtain the balance score and balance level, which is less efficient and redundant. In t...

A Novel Supervised Filter Feature Selection Method Based on Gaussian Probability Density for Fault Diagnosis of Permanent Magnet DC Motors.

Sensors (Basel, Switzerland)
For permanent magnet DC motors (PMDCMs), the amplitude of the current signals gradually decreases after the motor starts. In this work, the time domain features and time-frequency-domain features extracted from several successive segments of current ...