Search Results - (( using vectorization based algorithm ) OR ( automatic classification mining algorithm ))

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  1. 1

    Data mining of protein sequences with amino acid position-based feature encoding technique by Iqbal, M.J., Faye, I., Md Said, A., Samir, B.B.

    Published 2014
    “…In this paper, an amino acid position-based feature encoding technique is proposed to represent a protein sequence using a fixed length numeric feature vector. …”
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    Article
  2. 2

    Classification Of Gender Using Global Level Features In Fingerprint For Malaysian Population by Abdullah, Siti Fairuz

    Published 2016
    “…Two classification approaches which are the descriptive statistical and data mining are used in order to examine the classification of the gender by using the five extracted features. …”
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    Thesis
  3. 3

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…The increasing size of data being stored have created the need for computer-based methods for automatic data analysis. Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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    Thesis
  4. 4

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

    Published 2015
    “…A well known task is classification that predicts the class of new instances using known features or attributes automatically. …”
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    Thesis
  5. 5

    A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping by Althuwaynee, Omar F., Pradhan, Biswajeet, Park, Hyuck Jin, Lee, Jung Hyun

    Published 2014
    “…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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    Article
  6. 6

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

    Published 2016
    “…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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    Thesis
  7. 7

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Basically, the proposed of FUHS16, UHDS16 and UHDS8 algorithm produces the best motion vector estimation finding based on the block-based matching criteria. …”
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    Book Chapter
  8. 8

    Integration of object-based image analysis and data mining techniques for detailes urban mapping using remote sensing by Hamedianfar, Alireza

    Published 2015
    “…This algorithm represents the decision tree knowledge model, enables fast classification of intra-urban classes, and disables subjectivities related to the interaction with analysts. …”
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    Thesis
  9. 9

    Towards a better feature subset selection approach by Shiba, Omar A. A.

    Published 2010
    “…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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    Conference or Workshop Item
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    Enhanced ontology-based text classification algorithm for structurally organized documents by Oleiwi, Suha Sahib

    Published 2015
    “…This research combines the ontology and text representation for classification by developing five algorithms. The first and second algorithms namely Concept Feature Vector (CFV) and Structure Feature Vector (SFV), create feature vector to represent the document. …”
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    Thesis
  13. 13

    Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms by Afzal, Asif, Alshahrani, Saad, Alrobaian, Abdulrahman, Buradi, Abdulrajak, Khan, Sher Afghan

    Published 2021
    “…This work aims to model the combined cycle power plant (CCPP) using different algorithms. The algorithms used are Ridge, Linear regressor (LR), and support vector regressor (SVR). …”
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    Article
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    An ensemble data summarization approach based on feature transformation to learning relational data by Chung, Seng Kheau

    Published 2015
    “…The Information Gain borrowed from Information Retrieval theory and Term-term Correlation algorithm are used to determine the relevancy of these features to be selected or merged in order to form a new generation of TF-IDF vector space. …”
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    Thesis
  19. 19

    Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

    Published 2021
    “…There exist several types of classification algorithms, and these are based on various bases. The classification performance varies based on the dataset velocity and the algorithm selection. …”
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    Article
  20. 20

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

    Published 2024
    “…Based on the acquired results, the experiments reveal that the modified word vectors algorithm can effectively alter original LLM-generated word vectors to reflect intended contexts and can outperform baseline scores in contextual text classification tasks. …”
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    Thesis