Search Results - (( java implication tree algorithm ) OR ( tree evaluation learning algorithm ))

Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Performance evaluation for different intrusion detection system algorithms using machine learning by Zarir, Mustafa Nadhim

“…The objectives of this project is to evaluate the performance of various intrusion detection algorithms based on machine learning. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…This technique with k = 10 has been used in this thesis to evaluate the proposed approach. CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

“…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

“…The supervised machine learning algorithm, SVM and Decision Tree are used for the estimation of the mangrove age into young and mature. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms by Mutaz Hamed Hussien Khairi, Sharifah Hafizah Syed Ariffin, Nurul Mu'azzah Abdul Latiff, Kamaludin Mohamad Yusof, Mohamed Khalafalla Hassan, Fahad Taha Al-Dhief, Mosab Hamda, Suleman Khan, Muzaffar Hamzah

“…As a result, this paper presents several machine learning algorithms that include Decision Tree (DT), Support Vector Machine (SVM), Extremely Fast Decision Tree (EFDT) and Hybrid (DT-SVM) for detecting and classifying conflicting flows in SDNs. …”
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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

“…The performance of two top regression models, namely Extra Tree and AdaBoost was evaluated using six statistical evaluation metrics. …”

Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

“…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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Machine learning in predicting anti-money laundering compliance with protection motivation theory among professional accountants by Masrom, S., Tarmizi, M.A., Halid, S., Rahman, R.A., Abd Rahman, A.S., Ibrahim, R.

“…The research elaborates on the design and implementation of machine learning models based on three algorithms: Decision Tree, Gradient Boosted Tree, and Support Vector Machine. …”
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Streamflow Prediction Utilizing Deep Learning and Machine Learning Algorithms for Sustainable Water Supply Management by Latif S.D., Ahmed A.N.

Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

Visualisasi pohon sintaksis berasaskan model dan algoritma sintaks ayat bahasa Melayu by Yusnita, Muhamad Noor

“…These results proved that the algorithm and model, for syntactic tree output enhancement, are generalisable enough to be tested on other languages. …”
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Intelligent cooperative web caching policies for media objects based on decision tree supervised machine learning algorithm by Ibrahim, Hamidah, Yasin, Waheed, Abdul Hamid, Nor Asilah Wati, Udzir, Nur Izura

“…In this work, new intelligent cooperative web caching approaches based on decision tree supervised machine learning algorithm are presented. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…One of the most powerful machine learning methods to handle classification problems is the decision tree. …”
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Comparison of Gradient Boosting Decision Tree Algorithms for CPU Performance by Haithm Haithm, ALSHARI, Abdulrazak Yahya, Saleh, Alper, ODABAŞ

“…Gradient Boosting Decision Trees (GBDT) algorithms have been proven to be among the best algorithms in machine learning. …”
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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

“…Using metrics, this study evaluates Random Forest, ElasticNet, and Decision Tree algorithms. …”
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Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance by Alsariera Y.A., Baashar Y., Alkawsi G., Mustafa A., Alkahtani A.A., Ali N.

Evaluating Machine Learning Algorithms for Fake Currency Detection by Keerthana, S.N, Chitra, K.

“…Consequently, financial institutions like banks and ATMs require robust automated systems to accurately detect counterfeit currency. In this study, we evaluate the effectiveness of six supervised machine learning algorithms—K-Nearest Neighbor, Decision Trees, Support Vector Machine, Random Forests, Logistic Regression, and Naive Bayes—in detecting the authenticity of banknotes. …”
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Keylogger detection analysis using machine learning algorithm / Muhammad Faiz Hazim Abdul Rahman by Abdul Rahman, Muhammad Faiz Hazim

“…Besides, to test the accuracy of detection models on keylogger dataset comparing two machine learning algorithms. This study is carried out through the utilisation of two machine learning techniques, namely Decision Tree and Naive Bayes, on Jupyter Notebook in order to conduct an analysis of the Keylogger Detection dataset obtained from a trustworthy website known as Kaggle. …”
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