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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Thesis -
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Comparative analysis for topic classification in juz Al-Baqarah
Published 2018“…The SVM performance is then compared against other classification algorithms such as Naive Bayes, J48 Decision Tree and K-Nearest Neighbours. …”
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An intra-severity classification and adaptation technique to improve dysarthric speech recognition accuracy / Bassam Ali Qasem Al-Qatab
Published 2020“…Our proposed method introduces the intra-severity classification and adaptation techniques which are applied sequentially in two stages of system development. …”
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Classification of metamorphic virus using n-grams signatures
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…No EEG studies in Malaysia has been done on school children to study their emotional behaviour while learning. Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves
Published 2023“…This work shows that the spectroscopic measurement combined with classification techniques are promising strategy to classify severity level of WRD based on the spectral data of the rubber leaves.…”
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Book Section -
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Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli
Published 2017“…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
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8
Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm
Published 2014“…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
“…It leverages the Synthetic Minority Over-sampling Technique (SMOTE) to address the class imbalance in the dataset and employs a Voting Ensemble with soft voting to combine several base algorithms (Logistic Regression, Random Forest, Gradient Boosting, and XGBoost/SVM) for accurate prediction of mental health levels (normal, mild, moderate, severe, very severe). …”
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Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures
Published 2024“…This research introduces an innovative approach to Convolutional Neural Network (ConvNet) architecture generation through the utilization of the Symbiotic Organism Search ConvNet (SOS_ConvNet) algorithm. Leveraging the Symbiotic Organism Search optimization technique, SOS_ConvNet evolves ConvNet architectures tailored for diverse image classification tasks. …”
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An improved hybrid learning approach for better anomaly detection
Published 2011“…In this thesis, an improved hybrid mining approach is proposed through combination of K-Means clustering and classification techniques. K-Means clustering is an anomaly detection technique that is naturally capable for dealing with huge data in high speed network. …”
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13
An enhanced android botnet detection approach using feature refinement
Published 2019“…The experimental and statistical tests show that 97.28% accuracy achieved by Random Forest machine classifier, it performs well as compared to other classification algorithms. Based on the test results, various open research issues which need to be addressed in future studies are highlighted.…”
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Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation
Published 2013“…Linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbor (kNN), Naïve-Bayes (NB), artificial neural networks (ANNs) and support vector machines (SVMs) classification techniques, were tested to classify the leaf and trunk samples into four levels of disease severity. …”
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15
Spectral features selection and classification of oil palm leaves infected by Basal stem rot (BSR) disease using dielectric spectroscopy
Published 2018“…There is need for novel disease detection techniques that can be used to reduce the oil palm losses due to BSR. …”
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Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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FT-IR absorbance data for early detection of oil palm fungal disease infestation
Published 2012“…The selected principal component (PC) scores were used as input features in quadratic discriminant analysis (QDA) as a pattern recognition algorithm. The results indicated that QDA-based algorithm can distinguish between healthy and infected leaves at three stages of infection with high classification accuracies (>80%) when leaves demonstrated that the proposed technique has the potential for early detection of the Ganoderma disease.…”
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Sentiment analysis of customer review for Tina Arena Beauty
Published 2025“…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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Computer aided diagnoses for detecting the severity of Keratoconus
Published 2024“…Disease severity was categorized into three stages, namely, mild, moderate, and severe, according to the topographic KC classification by a senior ophthalmologist. …”
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