Feature selected based on PCA and optimized LMC
نویسندگان
چکیده
In this article, we propose an optimization algorithm for the original LMC [1] (Large Margin Classifier). We use PCA [2] (Principal Component Analysis) to reduce dimensionality of images, and then put data after reduction into optimized feature selection [3]. will get several features with greatest distinction. these classify images. Finally, experiment shows that accuracy under same dimensions is higher than LMC, in many cases, taking 6 vectors has exceeded highest LMC.
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ژورنال
عنوان ژورنال: MATEC web of conferences
سال: 2021
ISSN: ['2261-236X', '2274-7214']
DOI: https://doi.org/10.1051/matecconf/202133606034