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

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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…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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  2. 2
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…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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  3. 3
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…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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  4. 4
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…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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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  6. 6
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  7. 7
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…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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  8. 8
    An adaptive opposition-based learning selection: The case for jaya algorithm

    An adaptive opposition-based learning selection: The case for jaya algorithm by Nasser, Abdullah B., Kamal Z., Zamli, Hujainah, Fadhl, Ghanem, Waheed Ali H. M., Saad, Abdul-Malik H. Y., Mohammed Alduais, Nayef Abdulwahab

    Published 2021
    “…Over the years, opposition-based Learning (OBL) technique has been proven to effectively enhance the convergence of meta-heuristic algorithms. …”
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  9. 9
    Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours

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

    Published 2010
    “…The main problem in robotic system is in selecting the correct behaviour. The aim of this research is to overcome the behaviour selection problem. …”
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  10. 10
    Human odour detection approach using machine learning

    Human odour detection approach using machine learning by Ahmed Qusay Sabri

    Published 2019
    “…The unsurpassed framework for learning algorithm to be used for human identification is Levenberg-Marquardt backpropagation learning algorithm. …”
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  11. 11
    Development of lung cancer prediction system using meta-heuristic optimized deep learning model

    Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

    Published 2023
    “…Then different features are derived from the segmented region using Gray Intensity Co-Occurrence Distribution Matrix (GICDM) which is processed by applying a proposed Supervised Jaya Optimized Rough Set based Feature Selection (SJORSFS) algorithm. These algorithms select the best features according to the fitness value, and its redundancy is to be reduced. …”
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  12. 12
    Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting

    Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting by Loh, Eng Chuen

    Published 2021
    “…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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  13. 13
    High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor

    High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor by Abdul Rashid, Raghdah Rasyidah, Shaharudin, Shazlyn Milleana, Sulaiman, Nurul Ainina Filza, Zainuddin, Nurul Hila, Mahdin, Hairulnizam, Mohd Najib, Summayah Aimi, Hidayat, Rahmat

    Published 2024
    “…The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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  14. 14
    A systematic review of recurrent neural network adoption in missing data imputation

    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

    Published 2025
    “…Missing data is a pervasive challenge in diverse datasets accross various domains. …”
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  15. 15
    Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics

    Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi

    Published 2023
    “…The first step was to smooth out the data by using a filtering technique namely Savitzky-Golay to eliminate the noise of the spectrum. In order to select the most significant wavelengths, genetic algorithm (GA) was used as a forward feature selection technique. …”
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  16. 16
    An improved diabetes risk prediction framework : An Indonesian case study

    An improved diabetes risk prediction framework : An Indonesian case study by Sutanto, Daniel Hartono

    Published 2018
    “…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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  17. 17
    A systematic review of recurrent neural network adoption in missing data imputation

    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

    Published 2025
    “…Missing data is a pervasive challenge in diverse datasets, often resulting from human error, system faults, and respondent non-response. …”
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  18. 18
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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  19. 19
    A Novel Path Prediction Strategy for Tracking Intelligent Travelers

    A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

    Published 2009
    “…The FCM nodes are a novel selection of kinematical factors. Genetic algorithm (GA) is then used to train the FCM to be able to replicate the decisional behaviors of the intelligent traveler. …”
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  20. 20
    Towards personalized intensive care decision support using a Bayesian network: A multicenter glycemic control study

    Towards personalized intensive care decision support using a Bayesian network: A multicenter glycemic control study by Abu-Samah A., Razak N.N.A., Suhaimi F.M., Jamaludin U.K., Chase J.G.

    Published 2023
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