Problems Base course RU

Solves

clustering

Articles

ML Algorithm k-means Splits points into k groups so that points sit close to the centre of their group. O(n · k · d) per step 2 problems ML Algorithm DBSCAN Gathers dense regions of points of any shape into clusters and marks lone points as noise. O(n·Q + Σ|N(p)|) 2 problems

Problems

The nearest palette colour Clusters on a map of epicentres Lloyd's algorithm by the rules The density threshold

Often together

points 2 analytics 2 classic 2 interviews 2 iterative 1 randomized 1 images 1 nearest neighbour 1 hashing 1 geodata 1 science and physics 1