Diagnostic analysis is a technique used in machine learning and artificial intelligence to identify the root cause of a problem or undesired behaviour in a model or system. This technique involves the use of data analysis tools and techniques to determine the variables and characteristics that are contributing to the problem.
Diagnostic analysis is commonly used in machine learning to identify and solve problems with machine learning models, such as overfitting or underfitting. It is also used to identify problems in larger systems, such as poor performance or errors in decision-making.
Techniques used in diagnostic analysis include data exploration, correlation analysis, identification of outliers and hypothesis testing. Visualisation tools are also used to help identify patterns and trends in the data.
Diagnostic analysis is an important technique in machine learning and artificial intelligence, as it helps to identify and solve problems in models and systems. It is also an important technique in problem solving in general, as it provides a structured and systematic approach to identifying the root cause of a problem and finding effective solutions.
The content of this article synthesizes part of the chapter "Concept and brief history of Artificial Intelligence" of the thesis Generation of Artificial [...]
Read More »How is artificial intelligence helping us? Artificial intelligence (AI) has gone from being the stuff of science fiction movies to a [...]
Read More »In this article we are going to focus on how artificial intelligence (AI) can increase efficiency and reduce costs for your company by [...]
Read More »Industry 4.0 or the Fourth Industrial Revolution is based on the integration of digital technologies in the production and processing of goods and services.
Read More »
