Search Results - (( using evaluation process algorithm ) OR ( based classification learning algorithm ))

Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

“…Three defects categories and one non-defect were chosen for this evaluation. The key metrics for the evaluation are classification accuracy, classification precision and classification recall. 855 images were used to train and test the algorithms. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…This proposed classifier achieved 97.9% classification accuracy on the ISIC dataset. In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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Classification of JPEG files by using extreme learning machine by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

“…The algorithm automatically classifies the files based on evaluation measures of three methods Entropy, Byte Frequency Distribution and Rate of Change. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Extremal region selection for MSER detection in food recognition by Razali, Mohd Norhisham, Manshor, Noridayu, Abdul Halin, Alfian, Mustapha, Norwati, Yaakob, Razali

“…The performance of ERS algorithm is evaluated based on the classification performance metrics by using classification rate (CR), error rate (ERT), precision (Prec.) and recall (rec.) as well as the number of extremal regions produced by ERS. …”
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Crytojacking Classification based on Machine Learning Algorithm by Mansor W.N.A.B.W., Ahmad A., Zainudin W.S., Kama M.N., Madihah Mohd Saudi

Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…There are various decision tree algorithms, but the most commonly used are Iterative Dichotomiser 3 (ID3), CART, and C4.5. …”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

“…Theresult of this system using the iris dataset and credit card approval dataset to evaluate the proposed algorithm's accuracy, interpretability. …”
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Extreme learning machine classification of file clusters for evaluating content-based feature vectors by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

“…Consequently, an Extreme Learning Machine (ELM) neural network algorithm is used to evaluate the performance of the three methods in which it classifies the class label of the feature vectors to JPEG and Non-JPEG images for files in different file formats. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…To bridge this gap, a five-phase research methodology is structured to propose and evaluate an algorithm enabling the external modification of LLM-generated word vectors using scalar values as the focus weightage. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

“…In general, this thesis introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights by Seyed Vahid Moravvej, Roohallah Alizadehsani, Sadia Khanam, Zahra Sobhaninia, Afshin Shoeibi, Fahime Khozeimeh, Zahra Alizadeh Sani, Ru-San Tan, Abbas Khosravi, Saeid Nahavandi, Nahrizul Adib Kadri, N. Arunkumar, U.Rajendra Acharya, Muhammad Mokhzaini Azizan

Classification models for higher learning scholarship award decisions by Wirawati Dewi Ahmad, Azuraliza Abu Bakar

“…Each model was evaluated using technical evaluation metric, such contingency table metrics, and accuracy, precision, and recall measures. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…Studies have shown how user perception can have a strong influence on policies and decision-making processes in a place, society, and nation. This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

“…Several experiments were carried out by using different set of training and testing data-sets to evaluate the accuracy of the proposed model.As a result, the accuracy of the proposed model is considered excellent for academic leadership classification.For future work, in order to enhance the proposed bio-inspired classification model, a comparative study should be conducted using other established artificial immune system classification algorithms i.e. clonal selection and artificial immune network.…”
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Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

“…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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