AIMC Topic: Support Vector Machine

Clear Filters Showing 2321 to 2330 of 4975 articles

On the use of machine learning algorithms in forensic anthropology.

Legal medicine (Tokyo, Japan)
The classification performance of the statistical methods binary logistic regression (BLR), multinomial and penalized multinomial logistic regression (MLR, pMLR), linear discriminant analysis (LDA), and the machine learning algorithms naïve Bayes cla...

Predicting Gram-Positive Bacterial Protein Subcellular Location by Using Combined Features.

BioMed research international
There are a lot of bacteria in the environment, and Gram-positive bacteria are the most common ones. Some Gram-positive bacteria are very harmful to the human body, so it is significant to predict Gram-positive bacterial protein subcellular location....

Twin minimax probability machine for pattern classification.

Neural networks : the official journal of the International Neural Network Society
We propose a new distribution-free Bayes optimal classifier, called the twin minimax probability machine (TWMPM), which combines the benefits of both minimax probability machine(MPM) and twin support vector machine (TWSVM). TWMPM tries to construct t...

Development of prognostic model for patients at CKD stage 3a and 3b in South Central China using computational intelligence.

Clinical and experimental nephrology
BACKGROUND: Chronic kidney disease (CKD) stage 3 was divided into two subgroups by eGFR (45 mL/ min 1.73 m). There is difference in prevalence of CKD, racial differences, economic development, genetic, and environmental backgrounds between China and ...

Modified Support Vector Machine for Detecting Stress Level Using EEG Signals.

Computational intelligence and neuroscience
Stress is categorized as a condition of mental strain or pressure approaches because of upsetting or requesting conditions. There are various sources of stress initiation. Researchers consider human cerebrum as the primary wellspring of stress. To st...

Classification of Task-State fMRI Data Based on Circle-EMD and Machine Learning.

Computational intelligence and neuroscience
In the research work of the brain-computer interface and the function of human brain work, the state classification of multitask state fMRI data is a problem. The fMRI signal of the human brain is a nonstationary signal with many noise effects and in...

Raman spectroscopy of potential bio-hazards commonly found in bio-aerosols.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Pathogenic bio-aerosols are a threat to public health today, and thus quick detection and identification is of paramount importance. In this study, Raman spectroscopy was used to test 14 types of pollens, one type of fungus and two types of bacteria ...

Probing the neural dynamics of mnemonic representations after the initial consolidation.

NeuroImage
Memories are not stored as static engrams, but as dynamic representations affected by processes occurring after initial encoding. Previous studies revealed changes in activity and mnemonic representations in visual processing areas, parietal lobe, an...

Human Occupancy Detection via Passive Cognitive Radio.

Sensors (Basel, Switzerland)
Human occupancy detection (HOD) in an enclosed space, such as indoors or inside of a vehicle, via passive cognitive radio (CR) is a new and challenging research area. Part of the difficulty arises from the fact that a human subject cannot easily be d...

Milk Source Identification and Milk Quality Estimation Using an Electronic Nose and Machine Learning Techniques.

Sensors (Basel, Switzerland)
In this study, an electronic nose (E-nose) consisting of seven metal oxide semiconductor sensors is developed to identify milk sources (dairy farms) and to estimate the content of milk fat and protein which are the indicators of milk quality. The dev...