Search Results - (( program implementation model algorithm ) OR ( learning implementation learning algorithm ))

Rapid software framework for the implementation of machine learning classification models by Rahman, A.S.A., Masrom, S., Rahman, R.A., Ibrahim, R.

“…However, to implement a complete machine learning model involves some technical hurdles such as the steep learning curve, the abundance of the programming skills, the complexities of hyper-parameters, and the lack of user friendly platform to be used for the implementation. …”
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Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

“…This research aims to design and develop VR in learning programming algorithms. The ADDIE model is applied in this study to develop products through the stages of analysis, design, development, implementation, and evaluation. …”
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A new domain specific scripting language for automated machine learning pipeline by Masrom, S., Rahman, A.S.A., Omar, N., Baharun, N.

“…This paper concerns on two difficulties faced by non-expertsâ�� users in the utilization of machine learning; design of the model and the programming task for implementation. …”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

“…In this research, a hand-written character recognition model are implemented in C++ programming with ability to classify digits 0, 1, 2, and 3. …”
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Implementation of Health Monitoring System for Patients using Machine Learning Algorithms by Hariprasad, U.S., UshaSree, R.

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Early detection of heart disease using Random Forest Algorithm / Muhammad Iqbal Suhaidin ... [et al.] by Suhaidin, Muhammad Iqbal, Mohamed Yusoff, Syarifah Adilah, Johan, Elly Johana, Mydin, Azlina, Wan Mohamad, Wan Anisha

“…This potential has been investigated by thoroughly compared with several other studies across implementation of different types of dataset and algorithms. …”
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Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

“…This study has investigated five commonly used machine learning algorithm to be constructed as potential models for predicting stroke dataset. …”
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Students’ attitude towards video-based learning: machine learning analysis with rapid software / Abdullah Sani Abd Rahman ... [et al.] by Abd Rahman, Abdullah Sani, Meutia, Rita, Hamid, Yusnaliza, Abdul Rahman, Rahayu

“…In supporting the intervention approaches, machine learning techniques have been widely utilized. Another challenge is the difficulty to implement machine learning analysis by the educators. …”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

“…A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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Learning style analysis based on Felder-Silverman Index Model using Rule Base algorithm by Nurhakim, Muhammad, Ismail, Suhaila, Mohd Yusop, Nurhafizah Moziyana, Ahmad, Siti Rohaidah

“…The Rule Base algorithm is used to classify students based on their learning style characteristics. …”
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Flock optimization algorithm-based deep learning model for diabetic disease detection improvement by Balasubramaniyan, Divager, Husin, Nor Azura, Mustapha, Norwati, Mohd Sharef, Nurfadhlina, Mohd Aris, Teh Noranis

“…Hence, the research objective is to create an improved diabetic disease detection system using a Flock Optimization Algorithm-Based Deep Learning Model (FOADLM) feature modeling approach that leverages the PIMA Indian dataset to predict and classify diabetic disease cases. …”
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BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.

A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm by Anuar, Wadi Khalid, Lee, Lai Soon, Seow, Hsin Vonn, Pickl, Stefan

“…A matheuristic approach based on a reduced two-stage Stochastic Integer Linear Programming (SILP) model is presented. The proposed approach is suitable for obtaining a policy constructed dynamically on the go during the rollout algorithm. …”
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An interactive C++ programming courseware (SIFOO) / Mazliana Hasnan … [et al.] by Hasnan, Mazliana, Othman, Zainab, Mohamad, Norizan, Abdullah, Zamlina

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Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan by Mohd Hanis, Rani, Abdullah, Embong

“…The objective was to identify and implement the most accurate algorithm for the KPTM dataset and to come up with a good prediction model using decision tree technique. …”
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Experimental implementation controlled SPWM inverter based harmony search algorithm by Najeeb M., Mansor M., Razali R., Daniyal H., Yahaya J.A.F.

Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

“…Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

“…To generate the visual simulation in the simulator, the Python programming language is employed. The improved algorithm will help encourage the real-world implementation of DRL in many autonomous driving applications.…”
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Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging by Norhasmira, Mohammad, Anuar Mikdad, Muad, Rohana, Ahmad, Mohd Yusmiaidil, Putera Mohd Yusof

“…Nonetheless, a robust DCNN model was achieved as there is no sign of the model’s over-or under-ftting upon the learning process. …”
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