Questions

1. If two samples have a Minkowski distance (p=5) equal to 10, what can you say about their Manhattan distance?
2. The main factor that negatively impacts on the convergence speed of K-means is the dimensionality of the dataset. Is this correct?
3. One of the most important factors that can positively impact on the performance of K-means is the convexity of the clusters. Is this correct?
4. The homogeneity score of a clustering application is equal to 0.99. What does it mean?
5. What is the meaning of an adjusted Rand score equal to -0.5?
6. Considering the previous question, can a different number of clusters yield a better score?
7. An application based on KNN requires on average 100 5-NN base queries per minute. Every minute, 2 50-NN queries are executed (each of them requires 4 seconds with a leaf size=25) and, immediately after them, a 2-second blocking task is performed. Assuming...