Search Results - (( model evaluation model algorithm ) OR ( problem representation mining algorithm ))

Search alternatives:

Refine Results
  1. 1
    Evolving fuzzy grammar for crime texts categorization

    Evolving fuzzy grammar for crime texts categorization by Mohd Sharef, Nurfadhlina, Martin, Trevor

    Published 2015
    “…Machine learning (ML) based methods are the popular solution for this problem. However, the developed models typically provide low expressivity and lacking in human-understandable representation. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  2. 2
    Multitasking deep neural network models for Arabic dialect sentiment analysis

    Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

    Published 2022
    “…However, these approaches are based on simple sentence representation. Moreover, these models are based on single task learning (STL) and lack the ability to learn the relativity between different tasks (cross-task transfer) and modelling several polarities jointly, such as three and five polarities. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    An enhanced sequential exception technique for semantic-based text anomaly detection

    An enhanced sequential exception technique for semantic-based text anomaly detection by Taiye, Mohammed Ahmed

    Published 2019
    “…Text data are characterized by having problems related to ambiguity, high dimensionality, sparsity and text representation. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  4. 4
    Dissimilarity algorithm on conceptual graphs to mine text outliers

    Dissimilarity algorithm on conceptual graphs to mine text outliers by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

    Published 2009
    “…The graphical text representation method such as Conceptual Graphs (CGs) attempts to capture the structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these applications, it is necessary to measure the dissimilarity (or similarity) between knowledge represented in the CGs.In this paper, we would like to present a dissimilarity algorithm to detect outliers from a collection of text represented with Conceptual Graph Interchange Format (CGIF).In order to avoid the NP-complete problem of graph matching algorithm, we introduce the use of a standard CG in the dissimilarity computation.We evaluate our method in the context of analyzing real world financial statements for identifying outlying performance indicators.For evaluation purposes, we compare the proposed dissimilarity function with a dice-coefficient similarity function used in a related previous work.Experimental results indicate that our method outperforms the existing method and correlates better to human judgements. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  5. 5
    Compact structure representation in discovering frequent patterns for association rules

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, Norwati, Sulaiman, Md. Nasir, Othman, Mohamed, Selamat, Mohd Hasan

    Published 2002
    “…Frequent pattern mining is a key problem in important data mining applications, such as the discovery of association rules, strong rules and episodes. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  6. 6
    Compact structure representation in discovering frequent patterns for association rules

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, N., Sulaiman, M.N., Othman, M., Selamat, M.H.

    Published 2002
    “…Frequent pattern mining is a key problem in important data mining applications, such as the discovery of association rules, strong rules and episodes. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    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
    Conference Paper
    Save to List
    Saved in:
  8. 8
    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.…”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  9. 9
    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.…”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  10. 10
    USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING

    USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING by MUFLIKHAH, LAILIL

    Published 2010
    “…Based on the new representation, the documents are then subjected to the clustering algorithm itself, which is Fuzzy c-Means algorithm. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    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
    “…Having the ability to extract information from XML data would answer the problem of mining the web contents which is a very useful and required power nowadays. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  12. 12
    Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function

    Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

    Published 2012
    “…We resolve two non-trivial problems, i.e. semantic representation of text and the complexity of graph matching. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall

    Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall by Mustafa, M.R., Rezaur, R.B., Saiedi, Saied, Rahardjo, H., Isa, M.H.

    Published 2013
    “…The performance of four artificial neural network (ANN) training algorithms was evaluated to identify the training algorithm appropriate for modeling the dynamics of soil pore-water pressure responses to rainfall patterns using multilayer perceptron (MLP) ANN. …”
    Get full text
    Get full text
    Citation Index Journal
    Save to List
    Saved in:
  14. 14
    Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary

    Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary by Mohd Zamary, Nurul Aida

    Published 2024
    “…To evaluate the model, the model accuracy, precision, recall, F1- score, and confusion matrix were used. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting

    Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting by HASSAN, SAIMA

    Published 2013
    “…The outputs from the individual NN models were combined by four different aggregation algorithms in NNs ensemble. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  16. 16
    A Model for Evaluation of Cryptography Algorithm on UUM Portal

    A Model for Evaluation of Cryptography Algorithm on UUM Portal by Norliana, Abdul Majid

    Published 2004
    “…The purpose of this project are to construct and provide guidelines to develop a simulation model to evaluate cryptography algorithm in terms of encryption speed and descryption speed on UUM portal. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market

    Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

    Published 2024
    “…Therefore, this study focused to contribute on evaluating different algorithm models such as traditional ML and deep learning models with big stock data of multiple parameters from selected companies in Bursa Malaysia. …”
    thesis::master thesis
    Save to List
    Saved in:
  18. 18
    Evolutionary-based feature construction with substitution for data summarization using DARA

    Evolutionary-based feature construction with substitution for data summarization using DARA by Sia, Florence, Alfred, Rayner

    Published 2012
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  19. 19
    Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network

    Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network by Adam, A., Ibrahim, Z., Mokhtar, N., Shapiai, M.I., Mubin, M.

    Published 2016
    “…This study evaluates the performance of eye blink EEG signal peak detection algorithm for four different peak models which are Dumpala's, Acir's, Liu's, and Dingle's peak models. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network

    Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network by Asrul, Adam, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai, Marizan, Mubin

    Published 2016
    “…This study evaluates the performance of eye blink EEG signal peak detection algorithm for four different peak models which are Dumpala’s, Acir’s, Liu’s, and Dingle’s peak models. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: