AIMC Topic: Support Vector Machine

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Analysis and Comparison of Vector Space and Metric Space Representations in QSAR Modeling.

Molecules (Basel, Switzerland)
The performance of quantitative structure-activity relationship (QSAR) models largely depends on the relevance of the selected molecular representation used as input data matrices. This work presents a thorough comparative analysis of two main catego...

A Mature-Tomato Detection Algorithm Using Machine Learning and Color Analysis.

Sensors (Basel, Switzerland)
An algorithm was proposed for automatic tomato detection in regular color images to reduce the influence of illumination and occlusion. In this method, the Histograms of Oriented Gradients (HOG) descriptor was used to train a Support Vector Machine (...

Predicting Academic Performance of Students Using a Hybrid Data Mining Approach.

Journal of medical systems
Data mining offers strong techniques for different sectors involving education. In the education field the research is developing rapidly increasing due to huge number of student's information which can be used to invent valuable pattern pertaining l...

MLSeq: Machine learning interface for RNA-sequencing data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In the last decade, RNA-sequencing technology has become method-of-choice and prefered to microarray technology for gene expression based classification and differential expression analysis since it produces less noisy data....

Classification of degenerative parkinsonism subtypes by support-vector-machine analysis and striatal I-FP-CIT indices.

Journal of neurology
OBJECTIVES: To provide an automated classification method for degenerative parkinsonian syndromes (PS) based on semiquantitative I-FP-CIT SPECT striatal indices and support-vector-machine (SVM) analysis.

Predicting coronary artery disease: a comparison between two data mining algorithms.

BMC public health
BACKGROUND: Cardiovascular diseases (CADs) are the first leading cause of death across the world. World Health Organization has estimated that morality rate caused by heart diseases will mount to 23 million cases by 2030. Hence, the use of data minin...

A Novel Method for Classifying Liver and Brain Tumors Using Convolutional Neural Networks, Discrete Wavelet Transform and Long Short-Term Memory Networks.

Sensors (Basel, Switzerland)
Rapid classification of tumors that are detected in the medical images is of great importance in the early diagnosis of the disease. In this paper, a new liver and brain tumor classification method is proposed by using the power of convolutional neur...

Predicting miRNA-lncRNA interactions and recognizing their regulatory roles in stress response of plants.

Mathematical biosciences
It has been found that each non-coding RNA (ncRNA) can act not only through its target gene, but also interact with each other to act on biological traits, and this interaction is more common. Many studies focus mainly on the analysis of microRNA(miR...

Neural network and support vector machine for the prediction of chronic kidney disease: A comparative study.

Computers in biology and medicine
This paper aims to assist in the prevention of Chronic Kidney Disease (CKD) by utilizing machine learning techniques to diagnose CKD at an early stage. Kidney diseases are disorders that disrupt the normal function of the kidney. As the percentage of...