题目4267 · 机器学习
k-Means Assignment Step 2
A 1D cluster currently contains points [1,2,7]. What centroid does k-means assign to that cluster in the update step?
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中文题目题目4268 · 机器学习
k-Means Assignment Step 3
A 2D cluster contains points (0,0), (2,4), and (4,2). What centroid does k-means assign to that cluster?
打开 →题目4272 · 机器学习
k-Means Centroid Update 2
A 1D k-means step has current centroids 0 and 10, and the assigned points are {1,2} to the first cluster and {9} to the second. What are the updated centroids?
打开 →题目4266 · 机器学习
k-Means Assignment Step 1
A point in clustering has average within-cluster distance a=2 and smallest average distance to another cluster b=5. What is its silhouette score?
打开 →题目4269 · 机器学习
k-Means Assignment Step 4
A 2-component GMM has priors 0.6 and 0.4. At point x, the component likelihoods are 0.1 and 0.3. What posterior responsibility does component 2 get?
打开 →题目4270 · 机器学习
k-Means Assignment Step 5
A DBSCAN run uses minPts=5, counting the point itself. A point has 5 neighbors within eps. Is it a core point?
打开 →题目4271 · 机器学习
k-Means Centroid Update 1
In 1D, clusters A={0,2} and B={5,9}. What is their average-linkage distance?
打开 →题目4273 · 机器学习
k-Means Centroid Update 3
A cluster contains points [1,2,4]. What is its within-cluster SSE around the cluster mean?
打开 →题目4274 · 机器学习
k-Means Centroid Update 4
Under Ward linkage, what merge cost increase do two singleton clusters at positions 1 and 4 have in 1D?
打开 →题目4275 · 机器学习
k-Means Centroid Update 5
Clusters A={1,4} and B={6,8} are compared under complete linkage in 1D. What distance is used?
打开 →题目4287 · 机器学习
Why k-Means Struggles on Two Moons
Why can k-means behave poorly when one feature has a much larger scale than the others?
打开 →题目4286 · 机器学习
Why Scaling Matters for k-Means
You expect non-convex moon-shaped clusters plus some noise points. Would you try k-means or DBSCAN first, and why?
打开 →题目4283 · 机器学习
Average Linkage Distance 3
A 2D k-means run has centroids at (0,0) and (4,0). For point x=(1,2), which centroid is closer in the assignment step?
打开 →题目5039 · 机器学习
EM Mixture Diagnostic 24
Why can k-means and a Gaussian mixture with shared spherical covariances give similar clusters, yet still disagree on borderline points?
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