发明名称 METHOD AND APPARATUS FOR ACQUIRING TRAINING PARAMETERS FOR A MODEL
摘要 Method and device of selecting training parameters for training a model are disclosed. The method includes: (1) setting a precision requirement for the model, and a first parameter value interval defined by an upper limit and a lower limit; (2) obtaining a first value point and a second value point within the first parameter value interval; (3) obtaining and comparing respective first and second error rates by respectively setting the training parameter at the first and second value points for the model; (4) updating three values out of the upper limit, the lower limit, the first value point and the second value point; (5) repeating steps (3) and (4), until the precision requirement is net by the respective first and second value points; and (6) obtaining the optimal value of the training parameter.
申请公布号 US2016307115(A1) 申请公布日期 2016.10.20
申请号 US201615187571 申请日期 2016.06.20
申请人 Tencent Technology (Shenzhen) Company Limited 发明人 WU Xiaoping
分类号 G06N99/00;G06F17/11 主分类号 G06N99/00
代理机构 代理人
主权项 1. A method of selecting training parameters for training a model, comprising: at a device of having one or more processors and memory for storing one or more programs to be executed by the one or more processors: (1) setting a precision requirement for the model, and a first parameter value interval defined by an upper limit and a lower limit, the first parameter value interval being set wide enough to include an optimal value of a training parameter;(2) obtaining a first value point and a second value point within the first parameter value interval in accordance with a first predetermined formula, wherein the first value point is smaller than the second value point;(3) obtaining and comparing respective first and second error rates of the model by respectively setting the training parameter at the first and second value points for the model;(4) in accordance with a respective comparison result of comparing the respective first and second error rates, updating three values out of the upper limit, the lower limit, the first value point and the second value point, resulting in decreasing the first parameter value interval and a distance between the first value point and the second value point, wherein a relative order of the lower limit, the first value point, the second value point and the upper limit remains unchanged by the updating;(5) repeating steps (3) and (4), until the precision requirement is met by the respective first and second value points; and(6) when the precision requirement is met by the respective first and second error rates, obtaining the optimal value of the training parameter from between the first value point and the second value point in accordance with a second predetermined formula.
地址 Shenzhen CN