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 »Hoy, 3 de octubre, hemos estado en los prestigiosos "Premios SCALEUPS B2B organizada por la Fundación Empresa y Sociedad, para hablaros de la Medici [...]
Read More »Churn, or customer churn rate, is a constant challenge for today's businesses. The ability to retain customers is a constant challenge for today's companies.
Read More »You now have everything you need to get down to work and start working with your company's data. After overcoming the first few hurdles of the [...]
Read More »