Search Results - (( java application mining algorithm ) OR ( parameter visualization learning 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
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    Thesis
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    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
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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    Conference or Workshop Item
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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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    Final Year Project / Dissertation / Thesis
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  6. 6
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  7. 7
    Visual analysis to investigate the capability of ANFIS in modelling hydrological relationship using synthetic dataset

    Visual analysis to investigate the capability of ANFIS in modelling hydrological relationship using synthetic dataset by Ngahzaifa, Ab. Ghani, Zuriani, Mustaffa, Zafril Rizal, M Azmi

    Published 2018
    “…In using most of the machine learning algorithms including ANFIS, to obtain the best model, the common and normal approach is always by comparing models of different parameter settings based on the goodness-offit statistical measures. …”
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  8. 8
    Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah

    Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

    Published 2021
    “…In general, this thesis introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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  9. 9
    Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking

    Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking by Ong, Chor Keat

    Published 2017
    “…Until now, there are still no perfect algorithm to track the target flawlessly. In order to improve the performance, the main idea proposed is implementing optimization technique on the selected parameters and obtain a better performance. …”
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    Monograph
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  10. 10
    Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm

    Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

    Published 2020
    “…We applied a deep extreme learning machine approach to predict the user parameters. …”
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  11. 11
    Spectral analysis of discrete fourier transform (DFT) using Matlab

    Spectral analysis of discrete fourier transform (DFT) using Matlab by Wong Shen Yuong

    Published 2023
    “…In this project, signal is analyzed by applying Discrete Fourier Transform (DFT), specifically Fast Fourier Transform (FFT) algorithm in MATLAB. In the spectral analysis, the parameters are identified for signal analysis and the effect of varying the DFT parameters is studied. …”
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  12. 12
    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
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  13. 13
    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun

    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

    Published 2000
    “…This system is achieved using the Genetic Algorithm which is capable of performing information retrieval and learning algorithm. …”
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  14. 14
    Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms

    Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms by Nurellezia, Suleiman

    Published 2023
    “…The transformed data is then modelled using machine learning algorithms such as Naïve Bayes classifier and Support Vector Machine to predict the overall sentiment of tweets, in which the finding depicted an overall positive sentiment surrounding the issue. …”
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    Final Year Project Report / IMRAD
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  15. 15
    Extremal region selection for MSER detection in food recognition

    Extremal region selection for MSER detection in food recognition by Razali, Mohd Norhisham, Manshor, Noridayu, Abdul Halin, Alfian, Mustapha, Norwati, Yaakob, Razali

    Published 2021
    “…The visual analysis of foods on social media by using food recognition algorithm provides valuable insight from the health, cultural and marketing. …”
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  16. 16
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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  17. 17
    Vehicle Detection in Deep Learning

    Vehicle Detection in Deep Learning by Teoh, Per Nian

    Published 2019
    “…The objective of this project is vehicle detection with deep learning, so, vehicles data set from highway, urban road and housing area had been collected and applied to the deep learning and computer vision algorithms. …”
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  18. 18
    Exploration of COVID‑19 data in Malaysia through mapper graph

    Exploration of COVID‑19 data in Malaysia through mapper graph by Carey Ling, Yu Fan, Piau, Phang, Liew, Siaw Hong, Vivek Jason, Jayaraj, Benchawan, Wiwatanapataphee

    Published 2024
    “…A support vector-based feature selection and a heuristic approach for fine-tuning parameters internally within the algorithm are conducted. …”
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  19. 19
    Extremal Region Selection for MSER Detection in Food Recognition

    Extremal Region Selection for MSER Detection in Food Recognition by Mohd Norhisham Razali @ Ghazali, Noridayu Manshor, Alfian Abdul Halin, Norwati Mustapha, Razali Yaakob

    Published 2021
    “…The visual analysis of foods on social media by using food recognition algorithm provides valuable insight from the health, cultural and marketing. …”
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  20. 20
    The formulation of a transfer learning pipeline for the classification of the wafer defects

    The formulation of a transfer learning pipeline for the classification of the wafer defects by Lim, Shi Xuen

    Published 2023
    “…Automated processes have been used commonly in recent years, with the judgement done by using conventional image processing algorithm. However, limitations such as robustness and difficulty in setting up the parameters required for image processing algorithm encourages the investigation in using Deep learning classification in detecting the wafer defects. …”
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