Answer to Question #335551 in Microbiology for hani

Question

Exposure to weather can lead to a reduction in the performance and efficiency of photovoltaic systems. Researchers have used machine learning to develop a test which categorises solar panels as defective or non-defective, based on textural features of the solar cells extracted from thermal imaging [2].

In a sample of 260 solar panels, 130 were classified as defective by registered electrical power engineers. Of these, the machine learning test was able to correctly identify 126 defective solar panels. The test correctly classified all non-defective solar panels.

(a) Construct a binary classification table for the outcomes of the machine learning test, and calculate the sensitivity, specificity and accuracy of the test, showing all working.