Abstract: Feature selection is a big task and its challenge for high dimensional data. Semi-supervised feature selection is a combination of supervised and unsupervised data. Supervised data means labelled data and unsupervised data means unlabelled data. In semi-supervised feature selection unlabelled data is more than labelled data. Supervised learning means well labelled data that means data is already labelled with correct answer. Unsupervised data means that data is neither labelled nor classified and allowing algorithm to process without guidance. Supervised learning use processes like regression and classification. Algorithms used for unsupervised learning clustering and association. In supervised learning optimized performance criteria with the help of previous experience.
Keywords: Supervised, Semi-supervised, labelled, and unlabelled.
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DOI:
10.17148/IJARCCE.2021.10137
