Search Results - (( quality classification using algorithm ) OR ( using vector method algorithm ))

Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…Classification was performed using a Support Vector Machine (SVM) with a linear kernel. …”
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Performance evaluation of direction of arrival (DOA) for linear array antenna design using multiple signal classification (MUSIC) algorithm in variation of displacement vectors and... by Hamzah, Norhayati

“…In Smart Antenna system, the intelligence of the system depends on the information collected, processed and implemented through an algorithm i.e. Multiple Signal Classification (MUSIC). …”
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Vader lexicon and support vector machine algorithm to detect customer sentiment orientation by Vivine Nurcahyawati, ., Zuriani, Mustaffa

“…To accomplish this, a dataset from the Amazon website will be analyzed and classified using the Support Vector Machine algorithm. The objective of this method is to determine the level of customer orientation present within the dataset. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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Comparison of chemometrics methods for classification of sugarcane brix using visible and shortwave near-infrared technology by Ishkandar, C. D. M., Mat Nawi, Nazmi, Chen, Guangnan, Jensen, Troy, Mehdizadeh, Saman Abdanan

“…The results demonstrated that the VSWNIR spectroscopy together with chemometrics techniques could be a rapid tool to be used for classification of sugarcane quality based on spectral data.…”
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Partial discharge classification for XLPE cable joints using K nearest neighbors algorithm / Muhammad Shairazi Mohd Salleh by Muhammad Shairazi , Mohd Salleh

“…The extracted input features from the denoised signals were used to train the classifier. Classifications were also carried out using support vector machine (SVM) and artificial neural network (ANN) for comparison with KNN. …”
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Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

“…Support Vector Machine (SVM) is an efficient data mining approach for data classification. …”

Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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Training data selection for record linkage classification by Zaturrawiah Ali Omar, Zamira Hasanah Zamzuri, Noratiqah Mohd Ariff, Mohd Aftar Abu Bakar

“…Random forest and support vector machine classification algorithms were compared, and random forest with the top and imbalanced construction produced an F1 -score comparable to probabilistic record linkage using the expectation maximisation algorithm and EpiLink. …”
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Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve hig... by Harum, Norharyati, Khalil, Mohamad Kchouri, Obeid, Ali, Hazimeh, Hussein

“…In these approaches, machine learning techniques have been conducted to provide automatic classification and to improve accuracy. One of the most commonly used algorithms is Support Vector Machine (SVM). …”
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Application of slantlet transform based support vector machine for power quality detection and classification by Mohd Noh, Faridah Hanim, Miyauchi, Hajime, Yaakub, M. Faizal

“…The feature vectors of the PQ disturbances are then applied to SVM for the classification process. …”
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Application Of Slantlet Transform Based Support Vector Machine For Power Quality Detection And Classification by M. Noh, Faridah Hanim, Hajime, Miyauchi, Yaakub, Muhamad Faizal

“…The feature vectors of the PQ disturbances are then applied to SVM for the classification process. …”
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A Novel Feature Selection Method for Classification of Medical Data Using Filters, Wrappers, and Embedded Approaches by Saba Bashi, Irfan Ullah Khattak, Aihab Khan, Farhan Hassan Khan, Abdullah Gani, Muhammad Shiraz

“…Furthermore, classification is then performed on selected features to classify the data using a support vector machine (SVM) classifier. …”
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Protein structure prediction using robust principal component analysis and support vector machine by Zakaria, Nur Aini, Ali Shah, Zuraini, Kasim, Shahreen

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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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Using convolution neural networks for improving customer requirements classification performance of autonomous vehicle by Hao, Wang, Asrul, Adam, Fengrong, Han

“…Most of conventional algorithms, such as, Naive Bayes, MAXENT, and support vector machine (SVM), only use limited human engineered features and their accuracy for customized corpus in sentences classification are proven low which is less than 50 percent. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar by Anuwar, Fahteem Hamamy

“…After the feature extraction stage, Support Vector Machine (SVM) is used to classify the transient disturbance waveforms. …”
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