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  1. 1
    Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems

    Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems by Gunawan, Teddy Surya, Ambikairajah, Eliathamby

    Published 2012
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  2. 2
    A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping

    A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping by Ahmed Asal Kzar, Ahmed Asal Kzar, M Jafri, Mohd Zubir, Mutter, Kussay N., Anwar, Saumi Syahreza

    Published 2016
    “…The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. …”
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  3. 3
    Parallel implementation of genomic sequences classification using modified Gabor wavelet transform on multicore systems

    Parallel implementation of genomic sequences classification using modified Gabor wavelet transform on multicore systems by Gunawan, Teddy Surya, Ambikairajah, Eliathamby

    Published 2012
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  4. 4
    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia

    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia by San, Limhwee

    Published 2006
    “…The developed algorithms are two-band algorithm, terma linear and modified algorithm from the combination of the visible and infrared thermal bands. …”
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  5. 5
    A hybrid-based modified adaptive fuzzy inference engine for pattern classification

    A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

    Published 2011
    “…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
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  6. 6
    Modified word representation vector based scalar weight for contextual text classification

    Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

    Published 2024
    “…In addition, a contextual text classification experiment is conducted using benchmarked datasets to assess the performance of the modified word vectors in the targeted classification task. …”
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  7. 7
    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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  8. 8
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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  9. 9
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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  10. 10
    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification

    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

    Published 2020
    “…Thus, this study aims to adopt and modify the BFOA into Instance Selection (IS) classifier by manipulating its global search capability and high convergence rate for data classification problem. …”
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  11. 11
    Mutable composite firefly algorithm for gene selection in microarray based cancer classification

    Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

    Published 2022
    “…A computational approach for gene selection based on microarray data analysis has been applied in many cancer classification problems. …”
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  12. 12
    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification

    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

    Published 2018
    “…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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  13. 13
    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach

    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

    Published 2023
    “…Aerial photography; Aircraft detection; Antennas; Codes (symbols); Discrete cosine transforms; Discrete wavelet transforms; Glossaries; Image classification; Image coding; Image enhancement; Learning algorithms; Learning systems; Object recognition; Remote sensing; Satellite imagery; Satellites; Unmanned aerial vehicles (UAV); Discrete tchebichef transforms; Discriminative features; Finite Ridgelet Transform; Histogram of oriented gradients; Image processing and computer vision; Scale invariant feature transforms; SIFT; Sparse coding; Classification (of information)…”
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  14. 14
    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…Two modified algorithms are proposed in this research, which are mixture of the momentum algorithm with different learning rate algorithms. …”
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  15. 15
    Automated classification of blasts in acute leukemia blood samples using HMLP network

    Automated classification of blasts in acute leukemia blood samples using HMLP network by Harun, N. H., Mashor, M.Y., Abdul Nasir, A.S., Rosline, H.

    Published 2011
    “…This paper presents a study on classification of blasts in acute leukemia blood samples using artificial neural network.In acute leukemia there are two major forms that are acute myelogenous leukemia (AML) and acute lymphocytic leukemia (ALL).Six morphological features have been extracted from acute leukemia blood images and used as neural network inputs for the classification.Hybrid Multilayer Perceptron (HMLP) neural network was used to perform the classification task.The Hybrid Multilayer Perceptron(HMLP) neural network is trained using modified RPE(MRPE) training algorithm for 1474 data samples.The Hybrid Multilayer Perceptron (HMLP) neural network produces 97.04% performance accuracy.The result indicates the promising capabilities and abilities of the Hybrid Multilayer Perceptron (HMLP) neural network using modified RPE (MRPE) training algorithm for classifying and distinguishing the blasts from acute leukemia blood samples.…”
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  16. 16
    Maldroid- attribute selection analysis for malware classification

    Maldroid- attribute selection analysis for malware classification by Rahiwan Nazar, Romli, Mohamad Fadli, Zolkipli, Mohd Zamri, Osman

    Published 2019
    “…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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  17. 17
    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set

    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

    Published 2022
    “…Data pre-processing on the data set may improve the classification results. …”
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  18. 18
    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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  19. 19
    Logistic regression methods for classification of imbalanced data sets

    Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

    Published 2012
    “…Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. …”
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  20. 20
    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification

    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan C.H., Tan M.S., Chang S.-W., Yap K.S., Yap H.J., Wong S.Y.

    Published 2023
    “…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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