Search Results - (( data implication _ algorithm ) OR ( data classification using algorithm ))

Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

“…The research stage starts from pre-Processing, extraction, feature selection and classification processes and performance testing. Training and testing data in the study used a mixed model, namely data division, split model and cross validation. …”
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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network by Hairuddin, Nurul Liyana, Yusuf, Lizawati Mi, Othman, Mohd Shahizan

“…This was to obtain a good combination of parameters in order to produce a better gender classification. This study used 1,538 data samples from Goldman Osteometric Dataset which consisted of femur, humerus and tibia parts. …”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…For contextual text classification, the pre-trained LLM is further train on classificationspecific labeled data in a process called fine-tuning. …”
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Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary by Mohd Zamary, Nurul Aida

“…The phase of this project is divided into data preprocessing, implementation of the decision tree algorithm, and evaluation of the algorithm and prototype. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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Implementation of welch pre-processing in SVM algorithm for improved accuracy on EEG data by Hariyady Hariyady, Ag Asri Ag Ibrahim, Jason Teo, Muhammad Balya Firjaun Barlaman, Muhammad Aulanas Bitaqwa, Azhana Ahmad, Fouziah Md Yassin, Carolyn Salimun, Ng, Giap Weng

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Evaluation of principal component analysis for reducing seismic attributes dimensions: Implication for supervised seismic facies classification of a fluvial reservoir from the Mala... by Babikir, I., Elsaadany, M., Sajid, M., Laudon, C.

“…We train and test support vector machine (SVM), random forest (RF), and neural network (NN) algorithms that are widely used in seismic facies classification. …”
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Systematic review for phonocardiography classification based on machine learning by Altaf, Abdullah, Mahdin, Hairulnizam, Alive, Awais Mahmood, Ninggal, Mohd Izuan Hafez, Altaf, Abdulrehman, Javid, Irfan

“…This systematic review aims to examine the existing literature on phonocardiography classification based on machine learning, focusing on algorithms, datasets, feature extraction methods, and classification models utilized. …”
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Uncovering user perceptions toward digital banks in Indonesia: A Naïve Bayes sentiment analysis of twitter data by Karmagatri, Mulyani, Aziz, Clarisa Fezia Amanda, Asih, Wini Rizki Purnama, Jumbri, Isma Addi

“…The subsequent stages involved classification using the Naïve Bayes algorithm and word cloud visualization to identify the most commonly used words based on user responses. …”
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Consumer acceptance and perceptions of electric vehicles in Malaysia using sentiment analysis by Nor Farawahida Abdullah, Nur Haizum Abd Rahman

“…Key performance indicators, including accuracy, precision, and recall percentages, are used to assess the algorithm's performance. Results reveal that for the sentiment distribution, there is 55% positive and only 14% negative sentiment, while the remaining is neutral. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science by Balogun, A.-L., Tella, A., Baloo, L., Adebisi, N.

“…Air pollution is a global geo-hazard with significant implications, including deterioration of health and premature death. …”
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Systematic Review for Phonocardiography Classification Based on Machine Learning by Abdullah Altaf, Abdullah Altaf, Hairulnizam Mahdin, Hairulnizam Mahdin, Awais Mahmood Alive, Awais Mahmood Alive, Mohd Izuan Hafez Ninggal, Mohd Izuan Hafez Ninggal, Abdulrehman Altaf, Abdulrehman Altaf, Irfan Javid, Irfan Javid

“…This systematic review aims to examine the existing literature on phonocardiography classification based on machine learning, focusing on algorithms, datasets, feature extraction methods, and classification models utilized. …”
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A fuzzy approach for early human action detection / Ekta Vats by Ekta, Vats

“…The existing fuzzy implication operators are capable of handling only two dimensional data. …”
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Consumer acceptance and perceptions of electric vehicles in Malaysia using sentiment analysis by Nor Farawahida, Abdullah, Nur Haizum, Abd Rahman

“…Key performance indicators, including accuracy, precision, and recall percentages, are used to assess the algorithm's performance. Results reveal that for the sentiment distribution, there is 55% positive and only 14% negative sentiment, while the remaining is neutral. …”
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Analysis On QOS Parameters To Predict Http Response by A.Rahman, Khairulnizam

“…Therefore, the real live world web service label data uses to evaluate the focus parameters using classification machine learning algorithms to process the data. …”
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XAIRF-WFP: a novel XAI-based random forest classifier for advanced email spam detection by Bouke, Mohamed Aly, Alramli, Omar Imhemed, Abdullah, Azizol

“…The methodology incorporates data balancing through Hybrid Random Sampling, feature selection using the Gini Index, and a two-layer model explainability via Model-agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP) techniques. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…Since the 1960s, many algorithms for data classification have been proposed. …”
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