Classification of Chronic Obstructive Pulmonary Disease (COPD) Using Regression with Gabor Filtration and Random Forest Classification

In this paper, a lung tissue classification using Regression with Gabor Filtration and Random Forest Classification (RGRFC) method was created. For classification of the lung dataset, the random forest model has been used. The assessment of Lung Tissue shows promising outcomes in classification. The study offers assessment over COPD datasets to classify between moderate, normal and abnormal smokers. The technique has been tested for its precision, sensitivity and specificity for COPD Datasets. The result shows that the proposed method achieves higher precision, sensitivity and classifier than other methods.