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Selection, generation and extraction of MCCTree using XMCCTree
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Enhance efficiency of answering XML keyword query using incompact structure of MCCTree
Published 2012“…If the result cannot be used directly by the ranking method, the algorithm has an ineffective process. …”
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A Data Mining Approach to Construct Graduates Employability Model in Malaysia
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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Alternative Relative Discrimination Criterion Feature Ranking Technique for Text Classification
Published 2023“…To rank terms, most feature ranking algorithms, such as the Relative Discrimination Criterion (RDC) and Improved Relative Discrimination Criterion (IRDC), use document frequency (DF) and term frequency (TF). …”
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A data mining approach to construct graduates employability model in Malaysia
Published 2011“…The performance of Bayes algorithms are also compared against a number of tree-based algorithms. …”
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Prediction of employee promotion using hybrid sampling method with machine learning architecture / Shahidan Shafie, Soek Peng Ooi and Khai Wah Khaw
Published 2023“…In this study, there are eight machine learning algorithms have been used, such as Logistic Regression, Decision Tree, Random Forest, K-Nearest Neighbors, Support Vector Machine, Naïve Bayes, Adaptive Boosting Classifier, and Extreme Gradient Boost. …”
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Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree
Published 2021“…The proposed algorithm is used to fetch relevant features based from the high-dimensional input feature space. …”
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Provider independent cryptographic tools
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Monograph -
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
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Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…Then, the data is cluster by using K Means to produce labeled input that will be trained by using Gradient Boosting Machine, a decision tree algorithm to make prediction. …”
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Final Year Project -
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Footwear quality evaluation using decision tree and logistic regression models
Published 2022“…The objectives of the study are to determine the rank factors that affect the quality of footwear using decision tree methods. …”
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Thesis -
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Water optimization technique for precision irrigation system using IoT and machine learning
Published 2022“…The Spearman's rank correlation is used to receive the correlated values of real, and time series prediction. …”
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Prediction of novel doping agent through the integration of chemical and biological data using in silico method
Published 2016“…The internal validation showed that the combination of FCFP _ 4 and Decision Tree model performed best with a sensitivity value of 0.94 , when a cut off of rank 5 was applied. …”
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AnkPlex: algorithmic structure for refinement of near-native ankyrin-protein docking
Published 2017“…Subsequently, a re-scoring rank was generated by AnkPlex using a combination of a decision tree algorithm and logistic regression. …”
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Real-Time Video Processing Using Native Programming on Android Platform
Published 2012“…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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