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1. (WO2018166457) NEURAL NETWORK MODEL TRAINING METHOD AND DEVICE, TRANSACTION BEHAVIOR RISK IDENTIFICATION METHOD AND DEVICE

Pub. No.:    WO/2018/166457    International Application No.:    PCT/CN2018/078906
Publication Date: Fri Sep 21 01:59:59 CEST 2018 International Filing Date: Thu Mar 15 00:59:59 CET 2018
IPC: G06N 3/08
G06K 9/62
Applicants: ALIBABA GROUP HOLDING LIMITED
阿里巴巴集团控股有限公司
LI, Longfei
李龙飞
ZHOU, Jun
周俊
LI, Xiaolong
李小龙
Inventors: LI, Longfei
李龙飞
ZHOU, Jun
周俊
LI, Xiaolong
李小龙
Title: NEURAL NETWORK MODEL TRAINING METHOD AND DEVICE, TRANSACTION BEHAVIOR RISK IDENTIFICATION METHOD AND DEVICE
Abstract:
A neural network model training method and device, and a transaction behavior risk identification method and device. The neural network model training method comprises: inputting a plurality of pieces of pre-collected sample data into a gradient boosting decision tree (GBDT), so as to determine path information in the GBDT corresponding to each piece of sample data (S110); and according to the path information in the GBDT corresponding to each piece of sample data and a sample label, training a neural network model (S120). The method firstly determines the path information according to the GBDT, and then trains the neural network models according to the path information and the sample label. It is known from features of the GBDT itself that a certain piece of path information generally comprises multi-dimensional information of the sample data. Thus, the invention can improve the efficiency of training the neural network model.