TY - JOUR
T1 - Response to comment on "Quantifying long-term scientific impact"
AU - Wang, Dashun
AU - Song, Chaoming
AU - Shen, Hua Wei
AU - Barabási, Albert László
PY - 2014
Y1 - 2014
N2 - Wang, Mei, and Hicks claim that they observed large mean prediction errors when using our model. We find that their claims are a simple consequence of overfitting, which can be avoided by standard regularization methods. Here, we show that our model provides an effective means to identify papers that may be subject to overfitting, and the model, with or without prior treatment, outperforms the proposed naïve approach.
AB - Wang, Mei, and Hicks claim that they observed large mean prediction errors when using our model. We find that their claims are a simple consequence of overfitting, which can be avoided by standard regularization methods. Here, we show that our model provides an effective means to identify papers that may be subject to overfitting, and the model, with or without prior treatment, outperforms the proposed naïve approach.
UR - http://www.scopus.com/inward/record.url?scp=84904100396&partnerID=8YFLogxK
U2 - 10.1126/science.1248961
DO - 10.1126/science.1248961
M3 - Comment/debate
C2 - 25013055
AN - SCOPUS:84904100396
SN - 0036-8075
VL - 345
SP - 149c
JO - Science
JF - Science
IS - 6193
ER -