AIMC Topic: Support Vector Machine

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Machine learning in project analytics: a data-driven framework and case study.

Scientific reports
The analytic procedures incorporated to facilitate the delivery of projects are often referred to as project analytics. Existing techniques focus on retrospective reporting and understanding the underlying relationships to make informed decisions. Al...

Design and Implementation of Financial Service and Management Platform considering Support Vector Machine Algorithm.

Computational intelligence and neuroscience
With the rapid economic development, the financial industry has quietly become the leader of industries, the core and lifeblood of promoting economic development. At the same time, various financial services and management platforms emerge one after ...

Identification of DNA-binding proteins via Multi-view LSSVM with independence criterion.

Methods (San Diego, Calif.)
DNA-binding proteins actively participate in life activities such as DNA replication, recombination, gene expression and regulation and play a prominent role in these processes. As DNA-binding proteins continue to be discovered and increase, it is im...

Support vector machine embedding discriminative dictionary pair learning for pattern classification.

Neural networks : the official journal of the International Neural Network Society
Discriminative dictionary learning (DDL) aims to address pattern classification problems via learning dictionaries from training samples. Dictionary pair learning (DPL) based DDL has shown superiority as compared with most existing algorithms which o...

Comparing machine learning algorithms to predict 5-year survival in patients with chronic myeloid leukemia.

BMC medical informatics and decision making
INTRODUCTION: Chronic myeloid leukemia (CML) is a myeloproliferative disorder resulting from the translocation of chromosomes 19 and 22. CML includes 15-20% of all cases of leukemia. Although bone marrow transplant and, more recently, tyrosine kinase...

Identification of liquors from the same brand based on ultraviolet, near-infrared and fluorescence spectroscopy combined with chemometrics.

Food chemistry
Accurate identification of various liquors from the same brand is of great significance for safeguarding the rights and interests of consumers and the market economy. Here, the spectral properties of liquors were studied based on ultraviolet (UV), ne...

Evaluation of Three Feature Dimension Reduction Techniques for Machine Learning-Based Crop Yield Prediction Models.

Sensors (Basel, Switzerland)
Machine learning (ML) has been widely used worldwide to develop crop yield forecasting models. However, it is still challenging to identify the most critical features from a dataset. Although either feature selection (FS) or feature extraction (FX) t...

Decision-Tree-Initialized Dendritic Neuron Model for Fast and Accurate Data Classification.

IEEE transactions on neural networks and learning systems
This work proposes a decision tree (DT)-based method for initializing a dendritic neuron model (DNM). Neural networks become larger and larger, thus consuming more and more computing resources. This calls for a strong need to prune neurons that do no...

Capped Linex Metric Twin Support Vector Machine for Robust Classification.

Sensors (Basel, Switzerland)
In this paper, a novel robust loss function is designed, namely, capped linear loss function Laε. Simultaneously, we give some ideal and important properties of Laε, such as boundedness, nonconvexity and robustness. Furthermore, a new binary classifi...

Cloud Computing-Based Framework for Breast Tumor Image Classification Using Fusion of AlexNet and GLCM Texture Features with Ensemble Multi-Kernel Support Vector Machine (MK-SVM).

Computational intelligence and neuroscience
Breast cancer is common among women all over the world. Early identification of breast cancer lowers death rates. However, it is difficult to determine whether these are cancerous or noncancerous lesions due to their inconsistencies in image appearan...