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A GENERIC BINARY DECISION TREE GENERATOR AND QUERY SYSTEM Decision trees are so common that it would seem to be a useful expedient to write a Java program that builds and queries such trees The class presented in Table 1 does this with respect to binary decision trees The class has as one of its fields another class (an inner class) which defines a node.

Using ID3 Algorithm to build a Decision Tree to predict

A Decision Tree is a Flow Chart and can help you make decisions based on previous experience In the example a person will try to decide if he/she should go to a comedy show or not Luckily our example person has registered every time there was a comedy show in town and registered some information about the comedian and also registered if he/she went or not.

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Decision Tree is a supervised learning method used in data mining for classification and regression methods It is a tree that helps us in decisionmaking purposes The decision tree creates classification or regression models as a tree structure It separates a data set into smaller subsets and at the same time the decision tree is steadily developed.

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Why Use Decision Trees?Decision Tree TerminologiesAttribute Selection MeasuresPruning Getting An Optimal Decision TreeAdvantages of The Decision TreeDisadvantages of The Decision TreePython Implementation of Decision TreeThere are various algorithms in Machine learning so choosing the best algorithm for the given dataset and problem is the main point to remember while creating a machine learning model Below are the two reasons for using the Decision tree 1 Decision Trees usually mimic human thinking ability while making a decision so i.

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