CrossSpot algorithm code by Meng Jiang

Please keep confidential.

1. crossspot.py 1.1) set [c_local]: count of injected, foreground block, 1000 as default 1.2) generate_data(): generate random data and inject the block see global variables for data information: [MAX_NUM_SEED]: number of seeds in the algorithm [k_data]: number of modes [vec_n_local]: size vector of block [vec_n_global]: size vector of data [c_global]: capital C for count of the data 1.3) load_data(): load from file (data.csv) to a) data: entry list + value b) item2lineno: [k_data] maps, each map is {item:no. entry in [data] (lineno)} 1.4) CrossSpot Algorithm Output: screen output with best accuracy performance (maximum F1 score) with precision, recall and F1 average F1 score

2. crossspot-less-dense.py change [c_local] from 3000 down to 400, from denser block to less dense block: generate data run CrossSpot algorithm Output: in report.csv best accuracy performance avarage F1 score