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In decision analysis, a decision tree and the closely related influence diagram are used as a visual and analytical decision support tool, where the expected values (or expected utility) of competing alternatives are calculated. A decision tree consists of three types of nodes: [2] Decision nodes – typically represented by squares
DecideIT is a decision-making software for the Microsoft Windows operating system. It is based on multi-criteria decision making (MCDM) and the multi-attribute value theory (MAVT). It supports both value tree analysis for multi-attribute decision problems as well as decision tree analysis for evaluating decisions under risk and can combine ...
Decision trees used in data mining are of two main types: Classification tree analysis is when the predicted outcome is the class (discrete) to which the data belongs. Regression tree analysis is when the predicted outcome can be considered a real number (e.g. the price of a house, or a patient's length of stay in a hospital).
Like other decision trees, CHAID's advantages are that its output is highly visual and easy to interpret. Because it uses multiway splits by default, it needs rather large sample sizes to work effectively, since with small sample sizes the respondent groups can quickly become too small for reliable analysis. [citation needed]
A good summary of the capabilities of various software packages is available in the Decision Analysis Software Survey conducted by the Institute for Operations Research and the Management Sciences (INFORMS). The software packages listed in the survey range from free to commercial or enterprise-level packages.
LightGBM, short for Light Gradient-Boosting Machine, is a free and open-source distributed gradient-boosting framework for machine learning, originally developed by Microsoft. [4] [5] It is based on decision tree algorithms and used for ranking, classification and other machine learning tasks. The development focus is on performance and ...
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