My wish is to describe the time complexity of several clustering approaches. For example, suppose we have $n$ data points in $m$ dimensional space. Suppose further that the …

However, running a fixed number t of iterations of the standard algorithm takes only O(t*k*n*d), for n (d-dimensional) points, where kis the number of centroids (or clusters). This what practical …

Oct 13, 2019 · Hierarchical clustering algorithms are more versatile. Time Complexity and Space Complexity: Time complexity = O(n³) where n is the number of data points.

Feb 1, 2024 · This paper proposes algorithms with provable approximation bounds for building explainable clusterings. In addition, it investigates the price of explainability for these cost …

detection algorithms that consider factors such as the type of networks, the nature of com-munities, and applications. Despite numerous relevant review and survey papers, the literature …

We study the computational complexity of some explainable cluster-ing problems in the framework proposed by [Dasgupta et al., ICML 2020], where explainability is achieved via axis …

1-dimensional clustering problem can be solved efficiently. The complexity of most 2-dimenslonal clustering problems is not known. In this paper, we study the compu- tational complexity of …

Time Complexity of K-means •Let t dist be the time to calculate the distance between two objects •Each iteration time complexity: O(Knt dist) K = number of clusters (centroids) n = number of …

Jun 4, 2017 · Single linkage can be done in O (n) memory and O (n²) time. See the SLINK algorithm for details. It does not use a distance matrix. It depends on the implementation. For …

4 days ago · We strengthen this result by showing that inapproximability persists even when the fair-range constraints are trivially satisfiable, highlighting the intrinsic computational complexity …