Search Results - (( java implementation mining algorithm ) OR ( missing make learning algorithm ))

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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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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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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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset by Amirruddin, A., Aziz, I.A., Hasan, M.H.

“…Missing values in datasets is a synonymous problem in data mining which could lead to an incomplete dataset, making inaccurate predictions results in machine learning prediction processes. …”
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ExtraImpute: a novel machine learning method for missing data imputation by Alabadla, Mustafa, Sidi, Fatimah, Ishak, Iskandar, Ibrahim, Hamidah, Affendey, Lilly Suriani, Hamdan, Hazlina

“…In this paper, we propose a new imputation approach using Extremely Randomized Trees (Extra Trees) of machine learning ensemble learning methods named (ExtraImpute) to tackle numerical missing values in healthcare context. …”
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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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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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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

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Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours by Baneamoon, Saeed Mohammed Saeed

“…Overall, the enhanced approaches performed well and the enhanced learning processes proposed in the current study makes robot learning more effective. …”
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Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting by Loh, Eng Chuen

“…Next, a newly developed hybrid deep learning (DL) algorithm is proposed to predict the daily water level in selected rivers that flow through Kelantan. …”
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A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

“…Missing data is a pervasive challenge in diverse datasets accross various domains. …”
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

“…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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Predicting Breast Cancer Intelligently with Machine Learning Techniques by Manimozhi, I., Laksmi, D.

“…Feature selection methods are employed to extract the most relevant attributes influencing prediction performance. Multiple machine learning algorithms, such as Support Vector Machine (SVM), Random Forest, Naïve Bayes, Logistic Regression, and K-Nearest Neighbors (KNN), are implemented and compared. …”
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A review of knowledge graph embedding methods of TransE, TransH and TransR for missing links by Salwana, Mohamad, Noor Azida, Sahabudin, Nor Syahidatul Nadiah, Ismail, Ily Amalina, Ahmad Sabri

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Sentiment analysis of customer review for Tina Arena Beauty by Amri, Nur Najwa Shahirah

“…Customer review data were collected from multiple platforms and processed using Natural Language Processing (NLP) techniques such as Term Frequency-Inverse Document Frequency (TF-IDF). Three machine learning algorithms Naive Bayes, Random Forest, and Support Vector Machine (SVM) were evaluated, and SVM achieved the highest accuracy and was selected as the final classifier. …”
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Deep learning-based classification of breast tumors in ultrasound images / Ayub Ahmed Omar by Ayub Ahmed, Omar

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Predictive analytics for the sentiment of malaysian place of interest using machine learning models by Qiryn Adriana, Kharul Zaman

“…Furthermore, this study also trains three machine learning algorithms to predict the sentiment of textual data. …”
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Early Detection of Breast Cancer with Microcalcifications on Mammography Using Deep Learning by Ibrahim, Ashraf Osman, Abuharaz, Hafia Mamoun Ismail, Saleh, Mohammed A, Alharith, Razan

“…This study's contribution is the innovative use of advanced deep learning algorithms to a major issue in medical imaging, which represents a significant improvement over current diagnostic approaches. © 2025 IEEE.…”
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