Register

Go Classes | DA Course | Machine Learning

142 views
0 0 votes

Given the dataset: $(1,1),(3,3),(4,4),(5,5),(6,6),(9,9),(0,3),(3,0)$ and assuming the initial centroids for ( $K=3$ - means clustering) to be $C_1=$ $(3,3), C_2=(5,5)$ and $C_3=(6,6)$. One iteration of the Expectation Maximization Algorithm for K-means clustering, will update $C_3$ to ?

 

  1. $(15,15)$
  2. $(7.5,7.5)$
  3. $(6,6)$
  4. $(9,9)$

Please log in or register to answer this question.

Voting & Accepting an answer helps improve the community
Answer:
← Previous · GO Classes DA Test S...Next → · Go Classes | DA Cour...
← Previous in category · GO Classes DA Test S...Next in category → · Go Classes | DA Cour...
Position:
Show:

Related questions

0 0 votes
1 1 answer
263
263 views
GO Classes asked Apr 1, 2025
263 views
Go Classes | DA Course | Machine Learning
Perform the K-Medoid algorithm for $\mathrm{K}=2$ on the given dataset, assuming that points D and E are chosen as the initial medoid centers.
0 0 votes
1 1 answer
204
204 views
GO Classes asked Apr 1, 2025
204 views
Go Classes | DA Course | Machine Learning
A good way to pick the number of clusters, $k$, used for $k$-Means clustering is to try multiple values of $k$ and choose the value that minimizes the distortion measure....
0 0 votes
0 0 answers
174
174 views
GO Classes asked Apr 1, 2025
174 views
Go Classes | DA Course | Machine Learning
$\text { In which of the following plots are the points clustered by } k \text {-means clustering ? }$abboth a and bNeither a nor b
0 0 votes
0 0 answers
160
160 views
GO Classes asked Apr 1, 2025
160 views
Go Classes | DA Course | Machine Learning
Euclidean distance based $k$-means clustering algorithm was run on a dataset of 100 points with $k=3$. If the points $\left[\begin{array}{l}1 \\ 1\end{array}\right]$ and ...