I’m working on a python question and need guidance to help me understand better.
LINK TO THE PAGE: https://colab.research.google.com/drive/13hENX0V0I…(a) Linear Regression
We are given data used in a study of the homicide rate (HOM) in Detroit, over the years 1961-1973. The following data were collected by J.C. Fisher, and used in his paper ”Homicide in Detroit: The Role of Firearms,” Criminology, vol. 14, pp. 387-400, 1976. Each row is for a year, and each column are values of a variable.
(b) k-Nearest Neighbors
For this problem, you will be implementing the k-Nearest Neighbor (k-NN) classifier and evaluating on the Credit Approval (CA) dataset. It describes credit worthiness data (in this case, binary classification). (see http://archive.ics.uci.edu/ml/datasets/Credit+Approval) We have split the available data into a training set crx.data.training and a testing set crx.data.testing. These are both comma-separated text files (CSVs).
