Search
Search Results
-
An Adaptive Gaussian Kernel for Support Vector Machine
The most commonly used kernel function of support vector machine (SVM) in nonlinear separable dataset in machine learning is Gaussian kernel, also...
-
Cross Distance Minimization for Solving the Nearest Point Problem Based on Scaled Convex Hull
In pattern classification, the geometric method often provides a simple and intuitive solution. In the case of linear separability, solving the...
-
Optimization in Fuzzy Clustering: A Review
Fuzzy clustering effectively handles the problem of mystically separable data through fuzzy partitioning. Popularly known as soft clustering, fuzzy...
-
Terrain Classification of Hyperspectral Remote Sensing Images Based on SC-KSDA
To solve the problem of “same object but different spectrum” of hyperspectral remote sensing images and further extract more effective nonlinear...
-
Logic Elements and Neuron Networks
In this chapter logic elements with memory and artificial neuron networks, based on organic memristive devices, are discussed. It is considered...
-
Sparse L1-norm quadratic surface support vector machine with Universum data
In binary classification, kernel-free quadratic support vector machines are proposed to avoid difficulties such as finding appropriate kernel...
-
Basics of Machine Learning by Support Vector Machines
Here, we talk about the (machine) learning from empirical data (i.e., examples, samples, measurements, records, patterns or observations) by applying...
-
Nonlinear industrial process fault diagnosis with latent label consistency and sparse Gaussian feature learning
With the increasing complexity of industrial processes, the high-dimensional industrial data exhibit a strong nonlinearity, bringing considerable...
-
Hybrid CNN-SVM Model for Face Mask Detector to Protect from COVID-19
The 2019 coronavirus outbreak (COVID-19) has had a huge impact on humanity. By May 2021, nearly, 172 million people worldwide were affected by the...
-
An Enhancement in Accuracy for Breast Cancer Prediction Using Machine Learning and Deep Learning Model
As we are all aware, the population is growing rapidly in this modern period, placing a demand on the healthcare system to identify illnesses in the...
-
Emotion Classification Using Xception and Support Vector Machine
There has been a sudden increase in demand for algorithms or models to correctly and accurately identify human emotions. The conformity for machines...
-
Using Machine Learning to Protect Users Accounts in Twitter
Twitter is one of the most used social media sites where millions of people interact daily. Users perform tremendous tasks on Twitter, and it also...
-
Reduction of training data for support vector machine: a survey
Support vector machine (SVM) is a popular supervised machine learning technique extensively applied to various real-life applications. A weakness of...
-
In-process chatter detection in micro-milling using acoustic emission via machine learning classifiers
Predicting chatter stability in a micro-milling operation is challenging since the experimental identification of the tool-tip dynamics is a...
-
An Ensemble Machine Learning Approach to Classify Parkinson’s Disease from Voice Signal
The progressive nature of Parkinson’s disease (PD) means that it eventually affects all areas of the nervous system and the body that the nervous...
-
Implementation of Vibrations Faults Monitoring and Detection on Gas Turbine System Based on the Support Vector Machine Approach
PurposeGas turbines play a critical role in the gas and hydrocarbon industry, but they are prone to failures and malfunctions that can impact their...
-
High-impedance fault detection in power distribution grid systems based on support vector machine approach
Today, microgrids are used increasingly in different types because of its several financial and environmental benefits for customers, societies and...
-
Analog circuit diagnosis based on support vector machine with parameter optimization by improved NKCGWO
Support vector machine (SVM) is a widely used machine learning method in analog circuit fault diagnosis. However, SVM parameters such as kernel...
-
Support Vector Machine Optimization Using Secant Hyperplane Kernel
In the field of machine learning, one of the famous algorithms is support vector machines (SVM). It has been used to solve classification and as well...
-
Learning Cognitive Features to Classify EEG Signals for Mind-Controlled Locomotive
For a very long time, people have fantasized about making devices that can peer inside another person's mind and communicate with technology just by...