Evaluation of Machine Learning Algorithms using TOPSIS
2021
Machine Learning Algorithms.A subfield known as artificial intelligence (AI) and machine learning (ML) enables computers to "learn on their own" with training data and clearly planned without progressing over time.Data patterns can be found using machine learning algorithms, which can then be used to generate predictions on their own.The research methods and statistical models that computer systems use that are taught explicitly without a specific implementation of the task are known as machine learning (ML).Many of the programs have learning mechanisms that are used daily.A web search engine like Google is utilized frequently because it has a learning algorithm that learns how to rank websites.Numerous applications, including data mining, image processing, predictive analytics, etc., utilize these algorithms.The fundamental benefit of machine learning is that once an algorithm learns how to use the data, it will carry out its duties automatically.Algorithms that use machine learning can discover hidden patterns in data, forecast results, and get better at what they do with practice.As an example, simple linear regression is used to predict issues like stock market forecasts, while the KNN algorithm is used to solve classification problems.Different algorithms can be employed in machine learning for different purposes.TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) analysis using Algorithm 1, Algorithm 2, Algorithm 3, Algorithm 4, Algorithm 5, Algorithm 6, Algorithm 7 Alternative value and Radiologists 1, Radiologists 2, Radiologists 3, Radiologists 4 Evaluation Parameters in value.Algorithm 1, Algorithm 2, Algorithm 3, Algorithm 4, Algorithm 5, Algorithm 6, Algorithm 7. Radiologists 1, Radiologists 2, Radiologists 3, Radiologists 4. Radiologist 4 got the first rank whereas Radiologist 3, has the lowest rank.