DBSCAN Clustering or Apriori Association Rules Mining or Single Perceptron Neural Network

You should use no code that is not your own. (Consulting online references is ok, but do not copy their code. Also, if you do use a reference, ​cite it​.) Your assignment for this project is to implement one of the following three algorithms. Choice 1: DBSCAN Clustering Implement a program which will take many n­dimensional points, and the minPts and epsilon parameters, and return the result of the DBSCAN clustering algorithm. This should label all the points with their respective clusters. You may decide how you want your input/output formatted, but be specific on how to do this. Choice 2: Apriori Association Rules Mining Implement a program which will take many instances of itemsets, and find association rules among them. The program should take the itemsets as input, along with a desired support and confidence level. It should output the association rules in the form X => Y, where X is a set and Y is an item. Aside from these, you may decide how you want the input formatted, but be specific on how you want it. Choice 3: Single Perceptron Neural Network Implement a program which will take the instances of a training dataset (numeric attributes only), together with their desired outputs (again, numeric only) and train a single perceptron to learn the function. You should then be able to provide a test dataset without the desired outputs, and let the perceptron predict its output. You may decide how you want the input and output to be provided, but your program should be specific about how you want it. Also, the program must be capable of taking multiple passes at training the perceptron using the training data if necessary. If you need refreshers on these algorithms, you may ask me, or the wikipedia articles/textbook on these subjects are fairly helpful as well.