Ionian University, Corfu, Greece.
Adv Exp Med Biol. 2020;1194:239-242. doi: 10.1007/978-3-030-32622-7_21.
In many cases, the meaning of information is wrongly related to either the sense of data or the notion of knowledge. There is a crucial sequence of steps before information becomes knowledge and the value of data depends in the existence of information so as to produce knowledge. The most common method for producing knowledge through data is based on data analysis and primarily in the interpretation of results. This is the way humans make decisions, based on their existing knowledge, and thus using this method, they try to simulate several artificial decision tools. Decision trees (DTs) are such a tool. Their goal is consisted of automatic or semiautomatic big data analysis as well as creating new patterns. DT can be applied in various scientific fields such as bioinformatics. The most commonly used applications of decision trees are data mining and data classification. This study reviews these applications in bioinformatics.
在许多情况下，信息的意义要么与数据的意义相关，要么与知识的概念相关。在信息成为知识之前，有一个关键的步骤序列，而数据的价值取决于信息的存在，以便产生知识。通过数据分析主要是对结果的解释来产生知识是最常见的方法。这就是人类做出决策的方式，基于他们现有的知识，因此使用这种方法，他们试图模拟几种人工决策工具。决策树 (DT) 就是这样一种工具。它们的目标是自动或半自动的大数据分析以及创建新的模式。DT 可以应用于各个科学领域，如生物信息学。决策树最常用的应用是数据挖掘和数据分类。本研究回顾了生物信息学中的这些应用。
