[SOLVED] CS代写 TMLS22 format first

task 2 The aim of the assignment is to implement a decision tree induction algorithm for classification tasks and to demonstrate that it works as expected.It must be able to handle real-valued and nominal features. The algorithm does not need to handle missing values or real-valued target features (regression tasks). The student chooses whether to use information entropy or gini impurity as split criterion. To calculate binary splits for real-valued features, the following rule must be applied: an instance with a feature value lower than the mean feature value follows the left edge from the split node while all other instances follow the right edge from the split node.Demonstrate that the algorithm works as expected on three classification data sets: Iris
Download Iris, Wine
Download Wine, and one additional data set of your own choice from the UCI machine learning repository – you will have to bring it into the TMLS22 format first

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