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Intelligent Data Analysis: Understanding IDA, Tools, and Techniques, Slides of Public Health

Explore intelligent data analysis (ida), an interdisciplinary field focused on effective data analysis for extracting valuable information and knowledge from large datasets. Learn about ida concepts, tools like see5, cubist, illm, and magnum opus, and techniques for discovering rules hidden in data.

Typology: Slides

2012/2013

Uploaded on 11/21/2013

super-malik
super-malik 🇮🇳

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Download Intelligent Data Analysis: Understanding IDA, Tools, and Techniques and more Slides Public Health in PDF only on Docsity! Intelligent Data Analysis (IDA) docsity.com Interest and Excitement for Intelligent Data Analysis Decision making is asking for information and knowledge Data processing can give them Multidimensionality of problems is looking for methods for adequate and deep data processing and analysis docsity.com IDA is… … an interdisciplinary study concerned with the effective analysis of data; … used for extracting useful information from large quantities of online data; extracting desirable knowledge or interesting patterns from existing databases; docsity.com IDA or … Data mining Knowledge acquisition from data Genetic algorithm-based rule discovery Knowledge discovery Learning classifier system Machine learning etc. docsity.com IDA gives knowledge … docsity.com Knowledge in a domain can be expressed as a number of rules docsity.com Rule is … A formal way of specifying a recommendation, directive, or strategy, expressed as "IF premise THEN conclusion" or "IF condition THEN action". docsity.com How to discover rules hidden in the data? docsity.com Some tools for IDA … ILLM - the tool constructs classification models in the form of rules which represent knowledge about relations hidden in data. docsity.com Some tools for IDA … Magnum Opus - finds association rules providing competitive advantage by revealing underlying interactions between factors within the data. docsity.com Evaluation of IDA results Absolute & relative accuracy Sensitivity & specificity False positive & false negative Error rate Reliability of rules Etc. docsity.com See5…application… application.data - provides information on the training cases from which See5 will extract patterns. The entry for each case consists of one or more lines that give the values for all attributes. docsity.com See5…application… application.test - provides information on the test cases (used for evaluation of results). The entry for each case consists of one or more lines that give the values for all attributes. docsity.com See5…application…example… Epidemiological study (1970-1990) Sample of examinees died from cardiovascular diseases during the period Question: Did they know they were ill? 1 – they were healthy 2 – they were ill (drug treatment, positive clinical and laboratory findings) docsity.com See5…application…example… Results – example Rule 1: (cover 26) gender = M SBP > 111 oil_fat > 2.9 -> class 1 [0.929] docsity.com See5…application…example… Results – example Rule 4: (cover 14) smoking = Yes SBP > 131 glucose > 93 glucose <= 118 oil_fat <= 2.9 -> class 2 [0.938] docsity.com See5…application…example… Results – example Rule 15: (cover 2) SBP <= 111 oil_fat > 2.9 -> class 2 [0.750] docsity.com See5…application…example… Results – example Evaluation on test data (73 cases): (a) (b) <-classified as ---- ---- 43 1 (a): class 1 3 26 (b): class 2 docsity.com See5…application…example… Results – example (test set) Sensitivity=0.98 Specificity=0.90 docsity.com
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