Volume 19 No 6 (2021)
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Optimization of Machine Learning Model by Applying a Random Projection Algorithm for Breast Lesion Classification
Sonali Gupta
Abstract
Malignant and benign lesion classification is a challenging process that requires the best possible fusion of
several imaging parameters in relation to tissue density heterogeneity, prediction of lesion boundaries, and
change of surrounding tissues. Recent research has shown that important picture properties such as intensity,
energy, homogeneity, entropy, and statistical moments, among others, may be modelled using statistics and
texture features. As a result, this method was created to make early predictions about the identification of breast
lesions in digital image processing. Preprocessing, features extraction, and classification are among the phases
that make up the project. The main goal of the suggested technique is to categorise lesions into benign and
malignant categories. Additionally to enhance feature categorization
Keywords
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