Anomaly detection with adaptive auto grouping

A method of identifying anomalous behavior can include determining a first feature value and a second feature value of a series of numbers, identifying whether the determined first and second feature values map to a cell that is a part of a group based on spatial voting (SV) grid data, the SV grid data indicating an extent of each cell in a grid of cells, a number of rows and columns of cells in a group of cells, and, for each group of cells, a point in the center cell of the group of cells and a unique group number, and in response to identifying that the determined first and second feature values do not map to a cell of the grid of cells that is a part of a group, tagging the first and second feature values as corresponding to an anomalous behavior.