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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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A Predictive Classification Model For Running Injury by Ganesan, Devesh Raj

“…The J48, SMO, Random Forest, and Simple Logistic algorithms were used for 10-fold cross validation mode classification benchmarked on the ZeroR baseline algorithm. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Backpropagation vs. radial basis function neural model : Rainfall intensity classification for flood prediction using meteorology data by Chai, S.S., Wong, W.K., Goh, K.L.

“…The influence of the number of training data on the classification results was also analyzed. Results obtained showed, in term of classification accuracy, BPN model performed better than the RFN model. …”
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Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

“…For feature selection algorithms, SVM-FS model gave the best classification accuracies compared to GA and RF; ranged from 81.82% to 88.64% with SVM and kNN as the best classifiers. …”
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Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm by Liaghat, Shohreh, Mansor, Shattri, Ehsani, Reza, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja

“…The selected principal component scores were used in classification using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbor (kNN) and Naive-Bayes (NB) multivariate classification algorithms. …”
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Classification of Mental Health Level of Students Using SMOTE and Soft Voting Ensemble Classifier and the DASS-21 Profile by Muhammad Imron, Rosadi, Khoirun, Nisa, Nanik, Kholifah

“…The results demonstrate that the ensemble approach improves stability and accuracy compared to individual models. Notably, the application of SMOTE led to significant performance improvements, with classification accuracies reaching up to 100% for the Random Forest model. …”
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Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures by Jauro, Fatsuma, Abdullahi, Usman Ali, Abdulsalami, Aminu Onimisi, Ibrahim, Adamu Abubakar, Abdullahi, Mohammed, Chiroma, Haruna

“…Remarkably, the algorithm achieves remarkable accuracy while maintaining moderate model size.…”
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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

“…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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Early detection of basal stem rot disease (Ganoderma) in oil palms based on hyperspectral reflectance data using pattern recognition algorithms by Liaghat, Shohreh, Ehsani, Reza, Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja, Azam, Siti H. M. N.

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Moving vehicle noise classification using backpropagation algorithm by Norasmadi, Abdul Rahim, Paulraj, Murugesa Pandiyan, Assoc. Prof., Abdul Hamid, Adom, Assoc. Prof. Dr., Sundararaj, Sathishkumar

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Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq by Uzair , Ishtiaq

“…A Convolutional Neural Network (CNN) model was created from scratch for this study. Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Development of Deep Learning Classification Model for Diabetic Retinopathy Detection and Grading by Nurul Mirza Afiqah, Tajudin

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Spectral features selection and classification of oil palm leaves infected by Basal stem rot (BSR) disease using dielectric spectroscopy by Al-Khaled, Alfadhl Yahya Khaled, Abd Aziz, Samsuzana, Bejo, Siti Khairunniza, Mat Nawi, Nazmi, Abu Seman, Idris

“…Following the selection of significant frequencies, the features were evaluated using two classifiers, support vector machine (SVM) and artificial neural networks (ANN) to determine the overall and individual class classification accuracies. The selection model comparative feature analysis demonstrated that the best statistical indicators with overall accuracy (88.64%), kappa (0.8480) and low mean absolute error (0.1652) were obtained using significant frequencies produced by SVM-FS model. …”
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AI powered asthma prediction towards treatment formulation : An android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, Sarker, Md. Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md.

“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Sentiment analysis of customer review for Tina Arena Beauty by Amri, Nur Najwa Shahirah

“…Future work may involve expanding the dataset, integrating real-time feedback systems, and evaluating advanced algorithms to improve classification performance further. …”
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