Question
Consider a dataset of five observations given in the following table, each of which has two features f1 and f2:
| x₁ | x₂ | x₃ | x₄ | x₅ | |
|---|---|---|---|---|---|
| f₁ | 2 | 3 | 4 | 3 | 5 |
| f₂ | 6 | 7 | 5 | 4 | 6 |
Assume the number of cluster and the real number
. Also, assume the initial cluster centers as
and
. Apply fuzzy c-mean algorithm to find the modified cluster center after one iteration.
Answer :
Word Count : 430
The five data points are x₁ = (2,6), x₂ = (3,7), x₃ = (4,5), x₄ = (3,4), x₅ = (5,6). The initial cluster centers are V₁ = (1,1) and V₂ = (2,2). The fuzzifier is m = 2, and Euclidean distance is used. First, compute distances of each point from the two cluster centers. For x₁ = (2,6): d₁₁ = √[(2−1)² + (6−1)²] = √26 d₁₂ = √[(2−2)² + (6−2)²] = √16 = 4 For x₂ = (3,7): d₂₁ = √[(3−1)² + (7−1)²] = √40 d₂₂ = √[(3−2)² + (7−2)²] = √26 For x₃ = (4,5): d₃₁ = √[(4−1)² + (5−1)²] = √25 = 5 d₃₂ = _______ ___ __________ ___ ________ ______ _______ ________ ________ ________ _________ _________.
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The five data points are x₁ = (2,6), x₂ = (3,7), x₃ = (4,5), x₄ = (3,4), x₅ = (5,6). The initial cluster centers are V₁ = (1,1) and V₂ = (2,2). The fuzzifier is m = 2, and Euclidean distance is used. First, compute distances of each point from the two cluster centers. For x₁ = (2,6): d₁₁ = √[(2−1)² + (6−1)²] = √26 d₁₂ = √[(2−2)² + (6−2)²] = √16 = 4 For x₂ = (3,7): d₂₁ = √[(3−1)² + (7−1)²] = √40 d₂₂ = √[(3−2)² + (7−2)²] = √26 For x₃ = (4,5): d₃₁ = √[(4−1)² + (5−1)²] = √25 = 5 d₃₂ = _______ ___ __________ ___ ________ ______ _______ ________ ________ ________ _________ _________.
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