Search Results - (( java implementation mining algorithm ) OR ( basic evaluation tree algorithm ))

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  1. 1

    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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    Thesis
  2. 2

    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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    Article
  3. 3

    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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    Conference or Workshop Item
  4. 4

    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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    Conference or Workshop Item
  5. 5

    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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    Final Year Project / Dissertation / Thesis
  6. 6

    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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    Thesis
  7. 7

    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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    Thesis
  8. 8
  9. 9

    BMTutor research design: Malay sentence parse tree visualization by Muhamad Noor, Yusnita, Jamaludin, Zulikha

    Published 2014
    “…As a result of the lack of models and algorithms have been introduced in both parsers, the model and algorithm development phase is introduced in the design of BMTutor.Output from the development process shows that the prototype is able to provide sentence correction for all 15 invalid sentences and can produce parse tree visualizations for all 20 sentences used for prototype testing.…”
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    Conference or Workshop Item
  10. 10

    Image Based Oil Palm Tree Crowns Detection by Muhammad Afif Zakwan, Zaili

    Published 2020
    “…Image Based Oil Palm Tree Crowns Detection system is a basic system that enables the detection of oil palm tree crowns from red, green and blue (RGB) aerial images. …”
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    Final Year Project Report / IMRAD
  11. 11

    Reliability of bench-mark datasets for crowd analytic surveillance by Ameen, Mohamed Abul Hassan, Malik, Aamir Saeed, Nicolas, Walter, Faye , Ibrahima, Nordin, Nadira

    Published 2015
    “…The diverseness of these databases are assessed, with respect to the performance of the basic algorithms using qualitatively and quantitatively. …”
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    Conference or Workshop Item
  12. 12

    Reliability of bench-mark datasets for crowd analytic surveillance by Hassan, M.A., Malik, A.S., Nicolas, W., Faye, I., Nordin, N.

    Published 2015
    “…The diverseness of these databases are assessed, with respect to the performance of the basic algorithms using qualitatively and quantitatively. …”
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    Conference or Workshop Item
  13. 13

    Reliability of bench-mark datasets for crowd analytic surveillance by Hassan, M.A., Malik, A.S., Nicolas, W., Faye, I., Nordin, N.

    Published 2015
    “…The diverseness of these databases are assessed, with respect to the performance of the basic algorithms using qualitatively and quantitatively. …”
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    Conference or Workshop Item
  14. 14

    Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment by Wang, Kai, Zhou, Jun, Zhang, Wenhai, Zhang, Baohua

    Published 2021
    “…The algorithm defined in this study was evaluated with manual measurements as reference, and the morphological parameters of the canopy obtained using the LOAM and LeGO-LOAM algorithms as the basic framework were compared. …”
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    Article
  15. 15

    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

    Published 2024
    “…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”
    Conference Paper
  16. 16

    Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques by Jifroudi, Hamidreza Maskani

    Published 2021
    “…Therefore, in this research an algorithm has been created which can achieve the following goals. 1) To generate DTM only with LiDAR data without the need for layers and other information from the area 2) To create a building footprint from the LiDAR data by removing the tree cover effect 3) To create an automatic system that can perform the production process of DTM and footprint without the intervention of an expert. …”
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    Thesis
  17. 17

    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

    Published 2021
    “…The extracted features are evaluated through six machine learning (ML) classifiers namely softmax, k-nearest neighbor (kNN), support vector machine, linear discriminant analysis, decision tree, and naive Bayes. …”
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    Thesis