A practical guide to using Intelligent Data Analysis to help solve common life problems presented by data analysis tools

In Intelligent Data Analysis, the authors have collected insightful knowledge on the complex topics of data abstraction, machine learning, pattern recognition, and specialized statistical analysis. In-depth information has been crafted to be understood by students and professionals alike, providing an overall look at the tools needed to solve problems resulting from automated data collection.

Intelligent Data Analysis discusses common issues found in computer-based patient record-keeping, data warehousing tools, and intelligent alarm systems and presents methods of effective and efficient monitoring. The book provides readers with practical problem-solving insights to address typical issues faced in the engineering and medical fields specifically.

The text covers a variety of topics within Intelligent Data Analysis (IDA), including:

• Linear Regression and Decision Trees
• Interpretation of Black Box Models including Individual Conditional Expectations and Local Interpretable Model-agnostic Explanations
• An examination of IDA
• Applications of IDA and Machine Learning
• Model Interpretability

This exhaustive guide provides in-depth information on how IDA can be improved and implemented in engineering and biomedical applications for students, researchers, and professionals developing systems that include IDA technology.