阅读说明：本技术 分类模型训练方法、装置和计算机可读介质 (Classification model training method and device and computer readable medium ) 是由 周林飞 吴超华 丹尼尔·施内加斯 田鹏伟 李聪超 吴文超 于 2019-04-29 设计创作，主要内容包括：一种分类模型训练方法、装置和计算机可读介质,该分类模型训练方法包括：获取第一训练数据(101)；判断第一训练数据是否均衡(102)；如果第一训练数据不均衡,则向用户发送交互请求(103)；接收用户响应于交互请求的均衡化处理指令(104),其中,均衡化处理指令包括至少一个数据集标识,每一个数据集标识用于标识第一训练数据中导致第一训练数据不均衡的一个第一数据集；根据均衡化处理指令,分别针对每一个数据集标识所标识的第一数据集对第一训练数据进行均衡化处理,获得第二训练数据(105)；利用第二训练数据训练与目标设备相对应的分类模型(106)。该方法能够提高所训练出的分类模型的分类准确率。(A classification model training method, a device and a computer readable medium, wherein the classification model training method comprises the following steps: acquiring first training data (101); determining whether the first training data is equalized (102); if the first training data are not balanced, sending an interaction request to the user (103); receiving equalization processing instructions (104) of a user responding to the interaction request, wherein the equalization processing instructions comprise at least one data set identifier, and each data set identifier is used for identifying one first data set in the first training data, which causes the first training data to be unbalanced; according to the equalization processing instruction, respectively carrying out equalization processing on the first training data aiming at the first data set identified by each data set identification to obtain second training data (105); a classification model (106) corresponding to the target device is trained using the second training data. The method can improve the classification accuracy of the trained classification model.)