Search Results - (( java implication based algorithm ) OR ( affecting machine learning algorithm ))

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

“…The outcome of this study will add to the body of knowledge the most important and recent proposed solutions to mitigate SQL injection attack, in particular those based on machine learning algorithm…”
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Zarir, Abdullah Ahmad

“…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the conventional machine learning algorithms.…”
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Machine learning: tasks, modern day applications and challenges by Aljuaid, Lamyaa Zaed, Koh, Tieng Wei, Sharif, Khaironi Yatim

“…These machine learning algorithms are a collection of complex mathematical models and human intuitions. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Machine learning approach for automated optical inspection of electronic components by Lim, Siew Kee

“…The factor that affecting the confidence level of the supervised machine learning algorithm is discussed. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…Machine learning algorithms have widely been adopted recently to enhance the performance of IDSs. …”
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A Systematic Review Of Machine Learning Algorithms For Mental Health Detection Using Social Media Data by Madina Amiri, Sundresan Perumal, Norita Md. Norwawi, Nurazah Ismail

A review of machine vision pose measurement by Xiaoxiao, Wang, Beng, Ng Seng, O. K. Rahmat, Rahmita Wirza, Sulaima, Puteri Suhaiza

“…It also suggests that the integration of machine learning techniques may improve the performance of machine vision pose measurement algorithms. …”
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A review of machine vision pose measurement by Xiaoxiao, Wang, Beng, Ng Seng, O. K. Rahmat, Rahmita Wirza, Sulaima, Puteri Suhaiza

“…It also suggests that the integration of machine learning techniques may improve the performance of machine vision pose measurement algorithms. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

“…To overcome these limitations, this research has proposed five machine learning algorithms namely Linear Regression, Lasso, Ridge, Random Forest and Decision Tree. …”
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Application of machine learning algorithms to predict the thyroid disease risk: an experimental comparative study by Islam, Saima Sharleen, Haque, Md Samiul, Miah, M. Saef Ullah, Sarwar, Talha, Nugraha, Ramdhan

“…For this reason, this study compares eleven machine learning algorithms to determine which one produces the best accuracy for predicting thyroid risk accurately. …”
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Cyberbullying detection: a machine learning approach by Yeong, Su Yen

“…Bag of Words model was used to convert text into numerical inputs. The machine learning algorithm, Support Vector Machine was chosen after comparing it with other algorithms such as Multinomial Naïve Bayes, Decision Tree Classifier, and Random Forest Classifier. …”
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Study of machine learning in computer vision using Raspberry Pi by Chong, Kah Luo

Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

“…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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Estimating Depressive Tendencies Of Twitter User Via Social Media Data by Loh, Hooi Teng

“…The twitter dataset can be used to test the level of depressive tendencies with three different machine learning algorithms. These three different machine learning algorithms which are Support Vector Machine, XGBoost, and Random Forest. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

“…These problems will occur because these fields are mainly used machine learning classifiers. However, machine learning accuracy is affected by the noisy and irrelevant features. …”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
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Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

“…An alternative method is proposed, utilizing machine learning algorithms. Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”

Design of efficient blue phosphorescent bottom emitting light emitting diodes by machine learning approach / Muhammad Asyraf Janai by Muhammad Asyraf , Janai

“…The feature importance describes the impact of any single parameter in a device based on the model and how it affects the device efficiency. The result of our experiment shows that Random Forest, a machine learning algorithm, produces the best fit to our dataset and hence able to make the most accurate prediction of device efficiency. …”
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