Using C# With no extensions to solve the tasks.
The software shall be designed for students studying the clustering methods in their university courses so, the intended users of software are university students and their teachers. As a rule, during their classes students first study the methods then solve tasks using manual calculations or software such as Ms Excel so they need special software to:
- check the results of their manual calculations.
- after studying clustering methods, us them to solve data analysis tasks.
We shall describe methods to be used by students and implemented in software using the following example We analyze data about nine countries:
| Country | C1 | C2 | C3 | C4 | C5 | C6 | C7 | C8 | C9 |
|---|---|---|---|---|---|---|---|---|---|
| Income per capita (thousand Euro) | 2.6 | 2.8 | 1.1 | 4.2 | 3.9 | 4.1 | 1.3 | 1.9 | 3.7 |
| Population having university education (%) | 19 | 23 | 17 | 30 | 30 | 35 | 20 | 24 | 32 |
Use K-means algorithm to subdivide the countries into the groups: 1) high income, high proportion of population having university education; 2) low income, low proportion of population having university education; 3) average income, average proportion of population having university education. Use the maximin algorithm to subdivide the countries into the groups. Interpret the resulting subdivision.
