A Fast Spatial Pool Learning Algorithm of Hierarchical Temporal Memory Based on Minicolumn’s Self-Nomination

Figure 11

Comparison of stability in the New York taxi passenger flow. Each node in the graph represents the proportion of inputs whose SDRs have not changed in the whole dataset compared with the results of the previous round of training. The dataset was trained for 10 rounds using different algorithms.