Search Results - (( knowledge implementation using algorithm ) OR ( data classification learning algorithm ))

Search alternatives:

Refine Results
  1. 1
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…In these experiments, all the training and testing data are represented as feature vectors. By using the proposed algorithm, the sparse coefficients are learned by exploiting the relationships among different multi-view features and leveraging the knowledge from multiple related tasks. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  2. 2
    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif

    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

    Published 2014
    “…Data mining is a widely used approach for knowledge discovery in machine learning. …”
    Get full text
    Get full text
    Research Reports
    Save to List
    Saved in:
  3. 3
    Document classification based on kNN algorithm by term vector space reduction

    Document classification based on kNN algorithm by term vector space reduction by Moldagulova A., Sulaiman R.B.

    Published 2023
    “…Classification (of information); Data handling; Data mining; Information retrieval systems; Learning algorithms; Text processing; Vectors; Document Classification; Space reductions; Text classifiers; Text mining; Textual data; Unstructured data; Vector spaces…”
    Conference Paper
    Save to List
    Saved in:
  4. 4
    Lung Nodules Classification Using Convolutional Neural Network with Transfer Learning

    Lung Nodules Classification Using Convolutional Neural Network with Transfer Learning by Abdulrazak Yahya, Saleh, Ros Ameera, Rosdi

    Published 2023
    “…The objectives of this study are to pre-process lung nodules data, develop a CNN with transfer learning algorithm, and analyse the effectiveness of CNN with transfer learning compared to standard of other methods. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding
    Save to List
    Saved in:
  5. 5
    Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]

    Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

    Published 2021
    “…This paper provides an empirical study report, that building price predictions are based on green building and other general determinants. This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  6. 6
    Comparison on machine learning algorithm to fast detection of malicious web pages

    Comparison on machine learning algorithm to fast detection of malicious web pages by Wan Nurul Safawati, Wan Manan, Mohd Nizam, Mohmad Kahar, Noorlin, Mohd Ali

    Published 2021
    “…Therefore, implementing the principle of the machine learning, which is training the classification algorithm will be perform to improve the detection accuracy. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  7. 7
    Identification model for hearing loss symptoms using machine learning techniques

    Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

    Published 2014
    “…This research presents an efficient way to facilitate the hearing loss symptoms diagnosis process by designing a symptoms identification model that efficiently identify hearing loss symptoms based on air and bone conduction pure-tone audiometry data. The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    Classification of cervical cancer using random forest

    Classification of cervical cancer using random forest by Bahirah, Mohd Bashah, Ku Muhammad Naim, Ku Khalif, Nor Azuana, Ramli

    Published 2022
    “…In this research, the cervical cancer risk classification model was used by using data mining approach which consider Decision Tree and Random Forest algorithm. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  9. 9
    An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions

    An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions by Gerhana, Yana Aditia

    Published 2025
    “…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  10. 10
    Feature Selection and Ensemble Meta Classifier for Multiclass Imbalance Data Learning

    Feature Selection and Ensemble Meta Classifier for Multiclass Imbalance Data Learning by Sainin, Mohd Shamrie, Alfred, Rayner, Alias, Suraya, Lammasha, Mohamed A.M.

    Published 2018
    “…The aim of this paper is to investigate the effects of combining feature selection and ensemble classifiers on the prediction performance in addressing the multiclass imbalance data learning .This research uses data obtained from the Malaysian medicinal leaf images shape data and three other large benchmark data sets in which six ensemble methods from Weka machine learning tool were selected to perform the classification task.These ensemble methods include the AdaboostM1, Bagging, Decorate, END, MultiboostAB, and Rotation Forest.In addition, five base classifiers were used; Naïve Bayes, SMO, J48, Random Forest, and Random Tree in order to examine the performance of the ensemble methods. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  11. 11
    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition

    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…The neural network learns the rough set’s upper and lower approximations as feature extractors simultaneously with classification. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  12. 12
    Risk prediction analysis for classifying type 2 diabetes occurrence using local dataset

    Risk prediction analysis for classifying type 2 diabetes occurrence using local dataset by Abd Rahman, M. Hafiz Fazren, Wan Salim, Wan Wardatul Amani, Abd-Wahab, Firdaus

    Published 2020
    “…This research aims to develop a robust prediction model for classification of type 2 diabetes mellitus (T2DM), with the interest of a Malaysian population, using several well-known machine learning algorithm such as Decision Tree, Support Vector Machine and Naïve Bayers. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    Propositional satisfiability method in rough classification modeling for data mining

    Propositional satisfiability method in rough classification modeling for data mining by Abu Bakar, Azuraliza

    Published 2002
    “…Total number rules generated for the best classification model is recorded where the 30% of data were used for training and 70% were kept as test data. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  14. 14
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  16. 16
    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome

    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

    Published 2014
    “…The classification performance of K1-K2-NN model was benchmarked against 13 commonly used classification models using repeated random sub-sampling crossvalidation on ACSEKI data set. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…In data mining, classification learning is broadly categorized into two categories; supervised and unsupervised. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  19. 19
    Problem restructuring in interger programming for reduct searching

    Problem restructuring in interger programming for reduct searching by Ungku Chulan, Ungku Azmi Iskandar

    Published 2003
    “…In effect, they are very useful in generating rules when solving the classification problem that is inherent in data mining. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  20. 20
    New Learning Models for Generating Classification Rules Based on Rough Set Approach

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: