Search Results - (( feature classification modelling algorithm ) OR ( java application sensor algorithm ))

A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…The four peak models are named as Dumpala, Acir, Liu, and Dingle models whereas the full features set model consists of 16 peak features. …”
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Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

“…The important step is to idealize the combined feature selection models by finding the best combination of search method and feature selection algorithms. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Feature Selection with Harmony Search for Classification: A Review by Norfadzlan, Yusup, Azlan, Mohd Zain, Nur Fatin Liyana, Mohd Rosely, Suhaila Mohamad, Yusuf

“…This paper gives a general review of feature selection with Harmony Search (HS) algorithm for classification in various application. …”
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An accurate infant cry classification system based on continuos hidden Markov model by Abdulaziz Y., Ahmad S.M.S.

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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Support Vector Machine (SVM) is a present day classification approach originated from statistical approaches.Two main problems that influence the performance of SVM are selecting feature subset and SVM model selection. …”
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Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

“…Such a finding indicates that bio-inspired algorithms can contribute in identifying the few most important features to be used in data mining model construction.…”
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Classification of hand gestures from EMG signals / Diaa Albitar by Albitar, Diaa

“…The outcome shows that classification model using K-NN algorithm with 14 features has the highest classification accuracy, sensitivity and predictivity of97.99%, 94.77% and 92.95% respectively compared to other models from SVM and CNN. …”
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Behavioural features for mushroom classification by Ismail, Shuhaida, Zainal, Amy Rosshaida, Mustapha, Aida

“…The Principal Component Analysis (PCA) algorithm is used for selecting the best features for the classification experiment using Decision Tree (DT) algorithm. …”
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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

“…Features are then enhanced by using Tree-based feature selection to reduce the size of each feature and, therefore, enhance classification performance. …”
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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…Three algorithms were used to accomplish the task of feature representation. …”
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PV fault classification: Impact on accuracy performance using feature extraction in random-forest cross validation algorithm by Muhamad Zahim, Sujod, Siti Nor Azlina, Mohd Ghazali, Mohd Fadzil, Abdul Kadir, Al-Shetwi, Ali Qasem

“…This paper introduces a Solar PV Smart Fault Diagnosis and Classification (SFDC) model that harnesses the Random Forest (RF) algorithm in conjunction with Cross-Validation (CV) and an optimized feature extraction (FE) set. …”
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Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals by Badaruddin, Muhammad, Mohd Falfazli, Mat Jusof, Mohd Ibrahim, Shapiai, Asrul, Adam, Zulkifli, Md. Yusof, Kamil Zakwan, Mohd Azmi, Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Norrima, Mokhtar

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Development of classification algorithms of human gait by Koh, Chee Hong

“…In addtion, after compared with other state-of-the-arts of gait classification algorithms, our proposed classification algorithm produced comparable results with other state-of-arts using a smaller dataset with fewer training features.…”
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Feature extraction using active appearance model algorithm with Bayesian classification approach by Nuruzzaman, Mohammad, Hussain, Azham, Mohamad Tahir, Hatim, Abu Seman, Mohamad Amir

“…This study enhances invariant recognition of human faces and analysis to improve face verification and identification performance using Active Appearance Model (AAM) for feature extraction with Bayesian classification approach. …”
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Development of a syncope classification algorithm from physiological signals acquired in tilt-table test by Gan, Ming Hong

“…There are 8 set of feature selection model has built and a total of 24 set of classifiers with 3 different type of classification techniques were developed. …”
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Security alert framework using dynamic tweet-based features for phishing detection on twitter by Liew, Seow Wooi

“…This model is then embedded into the detection algorithm together with the inclusion of dynamic tweet-based features which are not as part of the features used to train a classification model for phishing tweet detection. …”
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Fusion of moment invariant method and deep learning algorithm for COVID-19 classification by Ervin Gubin Moung, Chong, Joon Hou, Maisarah Mohd Sufian, Mohd Hanafi Ahmad Hijazi, Jamal Ahmad Dargham, Sigeru Omatu

“…This paper proposes a fusion of a moment invariant (MI) method and a DL algorithm for feature extraction to address the instabilities in the existing COVID-19 classification models. …”
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SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

“…But irrelevant and redundant features are the obstacle for classification algorithm to build an efficient detection model. …”
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