This my implementation of ID3 algorithm. The algorithm ID3 (Quinlan) uses the method top-down induction of decision trees. Given a set of classified examples a decision tree is induced, biased by the information gain measure, which heuristically leads to small trees. The examples are given in attribute-value representation. The set of possible classes is finite. Only tests, that split the set of instances of the underlying example languages depending on the value of a single attribute are supported.

ID3 C#\myID3.sln
......\myID3.suo
......\myID3
......\.....\bin
......\.....\...\Debug
......\.....\...\.....\adult+stretch.txt
......\.....\...\.....\adult-stretch.txt
......\.....\...\.....\myID3.exe
......\.....\...\.....\myID3.pdb
......\.....\...\.....\myID3.vshost.exe
......\.....\...\.....\playtennis.txt
......\.....\...\.....\test.txt
......\.....\...\.....\yellow-small.txt
......\.....\...\.....\yellow-small+adult-stretch.txt
......\.....\...\Release
......\.....\C4_5.cs
......\.....\ClassDiagram2.cd
......\.....\DecisionTree.cs
......\.....\ID3.cs
......\.....\myID3.csproj
......\.....\obj
......\.....\...\x86
......\.....\...\...\Debug
......\.....\...\...\.....\DesignTimeResolveAssemblyReferencesInput.cache
......\.....\...\...\.....\myID3.csproj.FileListAbsolute.txt
......\.....\...\...\.....\myID3.exe
......\.....\...\...\.....\myID3.pdb
......\.....\...\...\.....\ResolveAssemblyReference.cache
......\.....\...\...\.....\TempPE
......\.....\playtennis.txt
......\.....\Program.cs
......\.....\Properties
......\.....\..........\AssemblyInfo.cs
......\.....\Trainning.cs
......\.....\TreeNode.cs
......\.....\Validation.cs

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