Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (2)
  • Open Access


    Drift Detection Method Using Distance Measures and Windowing Schemes for Sentiment Classification

    Idris Rabiu1,3,*, Naomie Salim2, Maged Nasser1,4, Aminu Da’u1, Taiseer Abdalla Elfadil Eisa5, Mhassen Elnour Elneel Dalam6

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6001-6017, 2023, DOI:10.32604/cmc.2023.035221

    Abstract Textual data streams have been extensively used in practical applications where consumers of online products have expressed their views regarding online products. Due to changes in data distribution, commonly referred to as concept drift, mining this data stream is a challenging problem for researchers. The majority of the existing drift detection techniques are based on classification errors, which have higher probabilities of false-positive or missed detections. To improve classification accuracy, there is a need to develop more intuitive detection techniques that can identify a great number of drifts in the data streams. This paper presents an adaptive unsupervised learning technique,… More >

  • Open Access


    Germination Quality Prognosis: Classifying Spectroscopic Images of the Seed Samples

    Saud S. Alotaibi*

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1815-1829, 2023, DOI:10.32604/iasc.2023.029446

    Abstract One of the most critical objectives of precision farming is to assess the germination quality of seeds. Modern models contribute to this field primarily through the use of artificial intelligence techniques such as machine learning, which present difficulties in feature extraction and optimization, which are critical factors in predicting accuracy with few false alarms, and another significant difficulty is assessing germination quality. Additionally, the majority of these contributions make use of benchmark classification methods that are either inept or too complex to train with the supplied features. This manuscript addressed these issues by introducing a novel ensemble classification strategy dubbed… More >

Displaying 1-10 on page 1 of 2. Per Page