Grid-Based Clustering with Uniform Density
Algorithm 8.4 Basic grid-based clustering algorithm.
Define a set of grid cells.
Assign objects to the appropriate cells and compute the density of each cell.
Eliminate cells having a density below a specified threshold.
Form clusters from contiguous (adjacent) groups of dense cells.
Complete the following tasks:
Upload the dataset file simulation.csv (Links to an external site.) from the Module 6 to SAS Studio. The first 200 observations in the dataset were generated from a uniform distribution over a circle centered at (2,3) of radius 2, and the next 100 observations were generated from a uniform distribution over a circle centered at (6,3) of radius 1.
By writing appropriate SAS code, produce a scatterplot of the data. Your plot should look similar to the one shown in Figure 8.10 (page 646) in Introduction to Data Mining.
By writing appropriate SAS code, generate the point counts for grid cells. It should have 49 cells using a 7-by-7 grid. Refer to Table 8.2 (page 646) in Introduction to Data Mining.
For each part, take the screenshots of the SAS code(s) and SAS output(s) and paste them into a Word document. Include all relevant calculations and your answers to all assignment items and submit the document to Canvas for grading. Clearly label all elements in your submission. In addition, provide a short description of any challenge(s) you faced during this assignment.