Machine learning problem Since, I cant update the csv files here, I can send them byemail or update

Machine learning problem Since, I cant update the csv files here, I can send them byemail or update to github Decision trees. Throughout the course, we usually rely onimplementations of machine learning algorithms in Python’sscikit-learn library. This homework problem is very different: youare asked to implement the ID3 algorithm for building decisiontrees yourself. Refer to p. 56 in Mitchell for pseudocode of theID3 algorithm that you are expected to imple- ment. You are notallowed to use sklearn or any other library with a built-inimplementation of ID3. Your program should read in a training dataset, a test dataset(both as csv files), and the name of the target variable (=classification attribute), and output to the screen: • your decision tree in a readable format (see below) • itsaccuracy over the test set Two pairs of sample datasets are available on Canvas, in thefolder Files/homeworks/hw2, namely playtennis train.csv andplaytennis test.csv, and republican train.csv and republi- cantest.csv. The first line of the csv files contains the names of thefields. The target variable is not necessarily in the lastcolumn. Name your Python program It should take command-lineparameters for a file with training data, a file with test data,and the name of the target variable. In particular, it should runcorrectly when executing the following commands at thecommand-line: python playtennis_train.csv playtennis_test.csv playtennis and python republican_train.csv republican_test.csv republican The file in Files/homeworks/hw2 contains starter codethat visualizes a tree and computes accuracy. It will produce someoutput when run for the playtennis data (using the exact samecommand and arguments as written above). The output is nonsense, inthe sense that the tree is hard coded and not constructed based onthe data. You need to remove the tree = funTree() statement fromthe body of the id3(examples, target, attributes) function, andwrite a correct body for this function yourself. This is the onlypart of the starter code that you are expected to touch. You can ofcourse introduce your own additional functions as you deemappropriate. Your final program should also work for therepublican data and for other, similarly structured, datasets. Important notes: Write your code in Python 3. Python 3 is the first version ofPython in the history of the language to break backwardcompatibility. This means that code written for earlier versions ofPython probably won’t run on Python 3. I won’t be able to run andgrade your program if it is written in Python 2.x. Any version ofPython 3.x should be fine. I will not test your code on datasets with continuous-valuedattributes. Your implemen- tation of ID3 can assume that allattributes are discrete-valued. You are expected to use informationgain to guide the search for the best split attribute. Attached

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