TY  - JOUR
T1  - An Efficient Method for Identifying Users across Various Digital Devices using the ‎Modified XGboost Algorithm ‎
A1  - Milad Ashrafi
A1  - Morteza Mohammadi Zanjireh
JF  - specialty journal of electronic and computer sciences
JO  - SPEC. J. ELECTRON. COMPUT. SCI.
SN  - 2412-7485
Y1  - 2019
VL  - 5
IS  - 3
SP  - 75
EP  - 85
N2  - In the present study, the modified XGBoost algorithm is introduced for identifying ‎users across different digital devices. Then, it is implemented on a dataset and the ‎results are compared with the results of the decision tree, support-vector machine and ‎K-nearest neighbor algorithms. Using several experiments with different parameters, it ‎is proved that using 200 leaves and 1000 trees, the best result is achieved, which is the ‎accuracy rate of 99.94% and the corresponding running time is 5439.26 seconds.‎ The running time of the proposed algorithm is much greater as compared to the other ‎algorithms tested in the present study, so, it shows poor performance in running time. ‎But what makes this algorithm significant is its accuracy. According to the results, its ‎accuracy rate is nearly 100% for any number of input data. The proposed algorithm ‎shows that it can provide reliable results in the case of offline running where it does ‎not matter how much its computing speed is‎‎‎.
UR  - https://sciarena.com/article/an-efficient-method-for-identifying-users-across-various-digital-devices-using-the-modified-xgboost-algorithm
ER  -