Search Results - (( data selection method algorithm ) OR ( variable active learning algorithm ))

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  1. 1

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Thesis
  2. 2

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Monograph
  3. 3

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…The performance of ANNs depend on many factors, including the network structure, the selection of activation function, the learning rate of the training algorithm, and initial synaptic weight values, the number of input variables, and the number of units in the hidden layer. …”
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    Thesis
  4. 4

    Input significance analysis: Feature selection through synaptic weights manipulation for EFuNNs classifier by Hassan, Raini, Taha Alshaikhli, Imad Fakhri, Ahmad, Salmiah

    Published 2017
    “…Specifically for the classification process, Big Data can cause the classifiers to process longer than necessary, and the redundant or irrelevant data may misguide the learning classification algorithms to learn the random error or noise related to them. …”
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    Article
  5. 5

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…Three algorithms of Linear (PURELIN), hyperbolic tangent sigmoid (TANSIG) and logistic sigmoid (LOGSIG) activation functions were selected for output layer. …”
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    Thesis
  6. 6

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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    Thesis
  7. 7

    Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

    Published 2011
    “…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
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    Thesis
  8. 8

    Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…Meanwhile, real data analysis using water quality index displays excellent accomplishments when compared to other selection procedures.Consequently, iterative feasible generalized least squares method is regarded as a more suitable estimation method in this automated selection.It can also be seen that simultaneous selections outperform the individual selections.This strategy by executing simultaneous selection with iterative estimation method is therefore proven to outclass in this analysis.…”
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    Article
  9. 9

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…Some of the features may contain irrelevant information caused by data redundancy or by noise. A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. …”
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    Conference or Workshop Item
  10. 10

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

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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    Thesis
  11. 11

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…Results of the reviewed techniques show that attribute selection methods capable to resolve the limitations in ID3 algorithm and increase the performance of the method. …”
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    Article
  12. 12

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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    Thesis
  13. 13

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Experiments demonstrate that ensemble classifier learning method produces better accuracy mining data streams and selecting subset of relevant features comparing other single classifiers. …”
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    Thesis
  14. 14

    Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir by Mohamad Nasir, Nur Fitri Nabila

    Published 2013
    “…The experimental results show that our method can achieve better performance in clonal selection algorithm sentiment classification and the data collected cannot be used at once in this model because training data is very time-consuming if using all the data. …”
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    Thesis
  15. 15

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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    Thesis
  16. 16
  17. 17

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
    “…One such pre-processing algorithm in EDM is clustering. It is a widely used method in data mining to discover unique patterns in underlying data. …”
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    Thesis
  18. 18

    Performance comparison of feature selection methods for prediction in medical data by Mohd Khalid, Nur Hidayah, Ismail, Amelia Ritahani, Abdul Aziz, Normaziah, Amir Hussin, Amir 'Aatieff

    Published 2023
    “…This study analyzes filter, wrapper, and embedded feature selection methods for medical data with the predictive machine learn- ing algorithm, Random Forest and CatBoost. …”
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    Proceeding Paper
  19. 19

    AGENT MEETING SCHEDULER by ZAINAL ABIDIN, NURAINI

    Published 2011
    “…An agent meeting scheduler prototype then will be developed to prove that the selected algorithm is working properly. Qualitative research method is being used to gather necessary data on agent algorithm and this data will be used to select the suitable algorithm. …”
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    Final Year Project
  20. 20

    Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

    Published 2008
    “…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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    Article