Search Results - (( binary classification learning algorithm ) OR ( learning classification mining algorithm ))

An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

“…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

“…The proposed method is applied to 14 real world dataset from the machine learning repository. The algorithm’s performance is illustrated by the corresponding table of the classification rate. …”
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Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

“…In our method we have employed Support Vector Machine as one of the best machine learning algorithm for classification and we contribute a new fuzzy membership function thus removing the Support Vector Machine’s weakness points in NER precision and multi classification. …”
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Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

“…The existing approaches are based on traditional machine learning algorithms, such as support vector machine (SVM). …”
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Unsupervised logic mining with a binary clonal selection algorithm in multi-unit discrete Hopfield neural networks via weighted systematic 2 satisfiability by Romli, Nurul Atiqah, Zulkepli, Nur Fariha Syaqina, Kasihmuddin, Mohd Shareduwan Mohd, Zamri, Nur Ezlin, Rusdi, Nur 'Afifah, Manoharam, Gaeithry, Mansor, Mohd. Asyraf, Jamaludin, Siti Zulaikha Mohd, Malik, Amierah Abdul

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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing by Ramadhan, Rakhmat Sani

“…This research concerns on binary classification which is classified into two classes. …”
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Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

“…The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.…”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

“…A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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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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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…In data mining, classification learning is broadly categorized into two categories; supervised and unsupervised. …”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Classification of students' performance in computer programming course according to learning style by Norwawi N.M., Abdusalam S.F., Hibadullah C.F., Shuaibu B.M.

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Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

“…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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Analysis Of Personal Protective Equipment Classification Method Using Deep Learning by Siti Zahrah Nur Ain, Silopung

“…Based on the result, CNN algorithm is a good algorithm as the binary classification of PPE achieved high accuracy result.…”
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A direct ensemble classifier for imbalanced multiclass learning by Sainin, Mohd Shamrie, Alfred, Rayner

“…Researchers have shown that although traditional direct classifier algorithm can be easily applied to multiclass classification, the performance of a single classifier is decreased with the existence of imbalance data in multiclass classification tasks.Thus, ensemble of classifiers has emerged as one of the hot topics in multiclass classification tasks for imbalance problem for data mining and machine learning domain.Ensemble learning is an effective technique that has increasingly been adopted to combine multiple learning algorithms to improve overall prediction accuraciesand may outperform any single sophisticated classifiers.In this paper, an ensemble learner called a Direct Ensemble Classifier for Imbalanced Multiclass Learning (DECIML) that combines simple nearest neighbour and Naive Bayes algorithms is proposed. …”
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Comparison Performance of Qualitative Bankruptcy Classification based on Data Mining Algorithms by Nilam Nur Amir, Sjarif, Yee, Fang Lim, NurulHuda, Mohd Firdaus Azmi, Kamalia, Kamardin, Doris Wong, Hooi Ten, Hafiza, Abas, Mubarak-Ali, Al-Fahim

“…Knowledge discovery using data mining techniques are commonly applied in bankruptcy classification and prediction. …”
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