Search Results - (( java implementation mining algorithm ) OR ( binary classification bayes algorithm ))

Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

“…The experimental results show that Naive-Bayes classifier with web text extraction algorithm proves to be the best method for web text classification.…”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri by Shukri, Ahmad Adib Baihaqi

“…This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. …”
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Machine learning approach of predicting Airline flight delay using Naïve Bayes Algorithm / Ahmad Adib Baihaqi Shukri ... [et al.] by Shukri, Ahmad Adib Baihaqi, Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

“…The KNN and SVM algorithms were alsotrained and tested to complete the binary classification of flight delays for benchmarking purposes. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Pixel-based feature for android malware family classification using machine learning algorithms by Mohd Zamri, Osman, Rahiwan Nazar, Romli, Ahmad Firdaus, Zainal Abidin, Mohd Faaizie, Darmawan

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Classification of Cognitive Frailty in Elderly People from Blood Samples using Machine Learning by Idris, S., Badruddin, N.

“…The binary classification for Robust and Frail with MCI achieved the highest accuracy, with Gaussian Naïve Bayes showing the highest holdout method accuracy of 70.5, as well as the highest cross validation accuracy of 74. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…Using the NSL-KDD dataset for evaluation, the proposed method demonstrates superior performance compared to conventional algorithms and related deep learning techniques, achieving higher precision, recall, F1 scores and overall accuracy in both binary and multi-class classification tasks. …”
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Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals by Altaf, Hunain, Ibrahim, Siti Noorjannah, Mohd Azmin, Nor Fadhillah, Asnawi, Ani Liza, Walid, Balqis Hanisah, Harun, Noor Hasmiza

“…This study will ultimately contribute to society's development with improved robust machine learning algorithm for binary classification.…”
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A Steganalysis Classification Algorithm Based on Distinctive Texture Features by Hammad B.T., Ahmed I.T., Jamil N.

“…Therefore, in this research, we present a steganalysis classification method based on one of the texture features chosen, such as segmentation-based fractal texture analysis (SFTA), local binary pattern (LBP), and gray-level co-occurrence matrix (GLCM). …”

An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Hui, Bian, Chiew, Kang Leng

“…This study investigates the performance of various conventional machine learning algorithms, including decision trees, naive Bayes, naive Bayes trees, random forest, random trees, MLP, and SVM, in detecting network intrusions using binary and multi-classification approaches. …”
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Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study by Mujtaba, Ghulam, Shuib, Liyana, Raj, Ram Gopal, Rajandram, Retnagowri, Shaikh, Khairunisa

“…Finally, in text classification algorithms, support vector machine classifier outperforms random forest, Naive Bayes, k-nearest neighbor, decision tree, and ensemble-voted classifier. …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…The study employed two MLC frameworks: Problem Transformation methods (Binary Relevance, Classifier Chains, Label Power Set, and Calibrated Label Ranking) and Algorithm Adaptation. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

“…Therefore, a model called Multi-Tasking Learning based on Convolutional Hierarchical Attention Neural Network (MTL-CHAN) is proposed, comprising of (i) shared word encoder and word attention networks across classification tasks, (ii) task-specific layers with convolutional neural network-based attention (CNNA) on sentence-level; to handle the Arabic explicit negation words and improve the classification performance by training Arabic classification tasks (binary, ternary, and five) jointly. …”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

“…Machine learning offers a solution to these challenges, with support vector machines (SVM) being a popular choice for breast cancer diagnosis given its strength in binary classification, which suited well with the dataset used in this thesis. …”
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