For example, when using decision trees to present demographic information on customers, the marketing department staff can read and interpret the graphical representation of the data without requiring statistical knowledge. One of the advantages of decision trees is that their outputs are easy to read and interpret without requiring statistical knowledge. Other fields where decision trees can be applied include engineering, education, law, business, healthcare, and finance. They can help in determining appropriate strategies that will help a company achieve its intended goals. The use of a decision tree support tool can help lenders evaluate a customer’s creditworthiness to prevent losses.ĭecision trees can also be used in operations research in planning logistics and strategic management. Lenders also use decision trees to predict the probability of a customer defaulting on a loan by applying predictive model generation using the client’s past data. Serving as a support tool in several fields In the absence of decision trees, the business may spend its marketing market without a specific demographic in mind, which will affect its overall revenues. They can help streamline a marketing budget and make informed decisions on the target market that the business is focused on. Using demographic data to find prospective clientsĪnother application of decision trees is in the use of demographic data to find prospective clients. Historical data on sales can be used in decision trees that may lead to making radical changes in the strategy of a business to help aid expansion and growth. One of the applications of decision trees involves evaluating prospective growth opportunities for businesses based on historical data. Assessing prospective growth opportunities For example, the income of an individual whose income is unknown can be predicted based on available information such as their occupation, age, and other continuous variables. Continuous variable decision treeĪ continuous variable decision tree is a decision tree with a continuous target variable. The categories mean that every stage of the decision process falls into one category, and there are no in-betweens. For example, the categories can be yes or no. Categorical variable decision treeĪ categorical variable decision tree includes categorical target variables that are divided into categories. There are two main types of decision trees that are based on the target variable, i.e., categorical variable decision trees and continuous variable decision trees. Decision trees can be divided into two types categorical variable and continuous variable decision trees.The decision tree tool is used in real life in many areas, such as engineering, civil planning, law, and business.Decision trees are used for handling non-linear data sets effectively.
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