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  • Open Access


    Heterogeneous Ensemble Feature Selection Model (HEFSM) for Big Data Analytics

    M. Priyadharsini1,*, K. Karuppasamy2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2187-2205, 2023, DOI:10.32604/csse.2023.031115

    Abstract Big Data applications face different types of complexities in classifications. Cleaning and purifying data by eliminating irrelevant or redundant data for big data applications becomes a complex operation while attempting to maintain discriminative features in processed data. The existing scheme has many disadvantages including continuity in training, more samples and training time in feature selections and increased classification execution times. Recently ensemble methods have made a mark in classification tasks as combine multiple results into a single representation. When comparing to a single model, this technique offers for improved prediction. Ensemble based feature selections parallel multiple expert’s judgments on a… More >

  • Open Access


    Ensemble Variable Selection for Naive Bayes to Improve Customer Behaviour Analysis

    R. Siva Subramanian1,*, D. Prabha2

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 339-355, 2022, DOI:10.32604/csse.2022.020043

    Abstract Executing customer analysis in a systemic way is one of the possible solutions for each enterprise to understand the behavior of consumer patterns in an efficient and in-depth manner. Further investigation of customer patterns helps the firm to develop efficient decisions and in turn, helps to optimize the enterprise’s business and maximizes consumer satisfaction correspondingly. To conduct an effective assessment about the customers, Naive Bayes(also called Simple Bayes), a machine learning model is utilized. However, the efficacious of the simple Bayes model is utterly relying on the consumer data used, and the existence of uncertain and redundant attributes in the… More >

  • Open Access


    A Two-Step Approach for Improving Sentiment Classification Accuracy

    Muhammad Azam1, Tanvir Ahmed1, Rehan Ahmad2, Ateeq Ur Rehman3, Fahad Sabah1, Rao Muhammad Asif4,*

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 853-867, 2021, DOI:10.32604/iasc.2021.019101

    Abstract Sentiment analysis is a method for assessing an individual’s thought, opinion, feeling, mentality, and conviction about a specific subject on indicated theme, idea, or product. The point could be a business association, a news article, a research paper, or an online item, etc. Opinions are generally divided into three groups of positive, negative, and unbiased. The way toward investigating different opinions and gathering them in every one of these categories is known as Sentiment Analysis. The enormously growing sentiment data on the web especially social media can be a big source of information. The processing of this unstructured data is… More >

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