Hello, this is for Datascience Application. Below is a question from the textbook fundamentals of machine learning for predictive data analytics, chapter 5, ISBN: 978-0-262-02944-5.

Thank you very much for your help!

Below is a picture of the book and below that is the exercise 1 from chapter 5.

JOHN D. KELLEHER BRIAN MAC NAMEE AOIFE D'ARCY FUNDAMENTALS OF MACHINE LEARNING FOR PREDICTIVE DATA ANALYTIC ALGORITHMS, WORKED EXAMPLES, AND CASE STUDIE * 6 You have been asked by a San Francisco property investment company to create a predictive model that will generate house price estimates for prop- erties they are considering purchasing as rental properties. The table below lists a sample of properties that have recently been sold for rental in the city. The descriptive features in this dataset are SIZE (the property size in square feet) and RENT (the estimated monthly rental value of the property in dollars). The target feature, PRICE, lists the prices that these properties were sold for in dollars PRICE ID SIZE RENT 1 2,700 9,235 2,000,000 1,315 1.800 820,000 3 1,050 1,250 800,000 4 2,.200 7,000 1,750,000 5 1,800 3,800 1,450,500 6 1,900 4,000 1,500,500 960 800 720,000 a. Create a k-d tree for this dataset. Assume the following order over the features: RENT then SIZE b. Using the k-d tree that you created in the first part of this question, find the nearest neighbor to the following query: SIZE = 1,000, RENT= 2,200