Decision trees are one of the most popular classifiers used in real-world applications due to their superior knowledge representation, robustness, ability to handle missing values, nonparametric induction, and ease of interpretation. Decision trees for data exploration •The most important attributes are at the top of the tree •Start each data mining project from exploring the most important attributes with decision trees • ID3 algorithm • Design issues • Split criteria • Stop criteria • Multi-valued attributes • Numeric attributes • … Alternatives may include not building the new product at all or bringing … The trees are also widely used as root cause analysis tools and solutions. Decision trees will help the organisation to have a look at all other alternatives if they do not want to build the product from scratch. As any other thing in this world, the decision tree has some pros and cons you should know. Decision trees are powerful tools that can support decision making in different areas such as business, finance, risk management, project management, healthcare and etc. Real Life Application: Decision Trees April 26 2011 A decision tree is an educational tool and is an effective way to teach the likely outcomes of projects and ideas. Learning algorithms are used to automatically induce a decision tree for specific domain problems. For example, an organisation is planning to build a new product. Decision trees help organisations to view alternatives to different events that can happen. A lot of resources and money will be invested in it. Companies are constantly making decisions regarding issues like product … The trees are “useful tools for helping you to choose between several courses of action. Advantages: Similarly, decision trees are also applicable to business operations.