Search Results - (( data classification using algorithm ) OR ( variable evaluation using algorithm ))

Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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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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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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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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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

“…The designed algorithm was structured in k-fold cross-validation in attempt to minimise the biasness of the classification performance, measured using error rate. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…The evaluation showed the overall superiority of VLBHO over the other algorithms in terms of accomplishing lower fitness values when optimizing mathematical functions of the variable length type.…”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…The evaluation showed the overall superiority of VLBHO over the other algorithms in terms of accomplishing lower fitness values when optimizing mathematical functions of the variable length type.…”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Sara, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

“…The evaluation showed the overall superiority of VLBHO over the other algorithms in terms of accomplishing lower fitness values when optimizing mathematical functions of the variable length type.…”
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Modeling forest fires risk using spatial decision tree by Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin, Sitanggang, Imas Sukaesih

“…This paper presents our initial work in developing a spatial decision tree using the spatial ID3 algorithm and Spatial Join Index applied in the SCART (Spatial Classification and Regression Trees) algorithm. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…Comparative evaluations with existing dropout methods demonstrated the superior performance of the proposed technique, particularly when applied within the Algorithm Adaptation framework using DNNs. …”
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Hybrid Genetic Algorithm On Predicting Next Rainfall Distribution by Mohd Zain, Rasuan

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Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi by Sherksi, Nasereddin Ibrahim

“…The data used in this thesis can be divided into two types. …”
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Towards personalized intensive care decision support using a Bayesian network: A multicenter glycemic control study by Abu-Samah A., Razak N.N.A., Suhaimi F.M., Jamaludin U.K., Chase J.G.

Comparison of meta-heuristic algorithms for fuzzy modelling of covid-19 illness’ severity classification by Nur Azieta, Mohamad Aseri, Mohd Arfian, Ismail, Abdul Sahli, Fakharudin, Ashraf Osman, Ibrahim, Shahreen, Kasim, Noor Hidayah, Zakaria, Sutikno, Tole

“…The performance of the five meta-heuristic algorithms was evaluated using the COVID-19 symptoms dataset. …”
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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

“…These methods are proposed to improve the descriptive accuracy of the summarized data. In the process of summarizing relational data, a genetic algorithm is also applied and several feature scoring measures are evaluated in order to find the best set of relevant constructed features. …”
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Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining by Termedi @ Termiji, Mohammad Izzuan

“…It proceeds through three phases of Need Analysis, Development of the Model and Evaluation of the Model. Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
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A new integrated approach for evaluating sustainable development in the electric vehicle sector by Lu, Wen Min, Chou, Chienheng, Ting, Irene Wei Kiong, Liu, Shangming

“…Second, this study conducts bootstrapped truncated regression to explore the impact of environmental, social, and governance (ESG) factors on the performance of the EV industry. Third, this study uses the classification & regression tree (CART), random forest, and eXtreme gradient boosting (XGBoost) algorithms to assist managers in identifying the key predictive variables for further classification and prediction. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators by Muazu Musa, Rabiu, Abdul Majeed, Anwar P.P., Taha, Zahari, Chang, Siow Wee, Ab. Nasir, Ahmad Fakhri, Abdullah, Mohamad Razali

“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. …”
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