Option #1 Grid-Based Clustering with Uniform Density First, carefully read Section 8.3 in Introduction to Data Mining . In this assignment, you will write SAS code to examine grid-based clustering...

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Option #1Grid-Based Clustering with Uniform Density

First, carefully read Section 8.3 inIntroduction to Data Mining. In this assignment, you will write SAS code to examine grid-based clustering algorithm. This algorithm is given on page 645 inIntroduction to Data Mining,and it is also provided below.

Algorithm 8.4 Basic grid-based clustering algorithm.

  1. Define a set of grid cells.
  2. Assign objects to the appropriate cells and compute the density of each cell.
  3. Eliminate cells having a density below a specified threshold.
  4. Form clusters from contiguous (adjacent) groups of dense cells.

Complete the following tasks:

  1. Upload the dataset filesimulation.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.
  2. 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) inIntroduction to Data Mining.
  3. 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) inIntroduction 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.

Your submission should be three to four pages in length and conform to theCSU Global Writing Center(Links to an external site.). Review the grading rubric to see how you will be graded for this assignment.

Answered 2 days AfterJan 23, 2021

Solution

Swapnil answered on Jan 25 2021
59 Votes
GRID/grid/cluster_remaining.husing namespace std;
void cluster_remaining_cy(int n,
int * closest_point,
int * result) {
/*
Label the remaining points by clustering them with the nearest
clustered neighbor.
Parameters
----------
n: Size of original dataset
closest_point: (n, ) a
ay with the index of the closest core point
result: (n, ) a
ay of cluster results to be calculated
*
for (int i = 0; i < n; i++) {
if (result[i] < 0) {
result[i] = result[closest_point[i]];
}
...
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