Abstract
The inductive learning algorithms are the very attractive methods generating hierarchical classifiers. They generate hypothesis of the target concept on the base on the set of labeled examples. This paper presents some of the decision tree induction methods, boosting concept and their usefulness for diagnosis of the type of hypertension (essential hypertension and five type of secondary one: fibroplastic renal artery stenosis, atheromatous renal artery stenosis, Conn’s syndrome, renal cystic disease and pheochromocystoma). The decision on the type of hypertension is made only on base on blood pressure, general information and basis biochemical data.
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Keywords
- Essential Hypertension
- Renal Artery Stenosis
- Boost Decision Tree
- Decision Tree Induction
- Renal Cystic Disease
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Wozniak, M. (2005). Boosted Decision Trees for Diagnosis Type of Hypertension. In: Oliveira, J.L., Maojo, V., Martín-Sánchez, F., Pereira, A.S. (eds) Biological and Medical Data Analysis. ISBMDA 2005. Lecture Notes in Computer Science(), vol 3745. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573067_23
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DOI: https://doi.org/10.1007/11573067_23
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