A method for detecting a state of a target mobile terminal, comprising: acquiring a state sample set of a plurality of sample mobile terminals, wherein the state sample set comprises n holding state samples collected by the plurality of sample mobile terminals when the plurality of sample mobile terminals are located in a preset holding space, and m non-holding state samples collected by the plurality of sample mobile terminals when the plurality of sample mobile terminals are not located in the preset holding space, where n and m are integers greater than zero, wherein the preset holding space comprises a pocket, a backpack, or a saddlebag taken by a user; determining a classification algorithm; acquiring a classifier by training using the state sample set determined as training data according to the classification algorithm; and sending the classifier to a target mobile terminal to be detected, in which the target mobile terminal is configured to determine whether the target mobile terminal is located in the preset holding space based on the classifier and according to a state sample of the target mobile terminal, wherein sending the classifier to the target mobile terminal comprises: performing a format conversion on the classifier, to enable the classifier to be suitable to an operation environment of the target mobile terminal; and sending the converted classifier to the target mobile terminal, characterized in that performing the format conversion on the classifier comprises: converting a binary file of the classifier in a spark format into a pmml file of the classifier in a pmml format. acquiring a state sample set of a plurality of sample mobile terminals, wherein the state sample set comprises n holding state samples collected by the plurality of sample mobile terminals when the plurality of sample mobile terminals are located in a preset holding space, and m non-holding state samples collected by the plurality of sample mobile terminals when the plurality of sample mobile terminals are not located in the preset holding space, where n and m are integers greater than zero, wherein the preset holding space comprises a pocket, a backpack, or a saddlebag taken by a user; determining a classification algorithm; acquiring a classifier by training using the state sample set determined as training data according to the classification algorithm; and sending the classifier to a target mobile terminal to be detected, in which the target mobile terminal is configured to determine whether the target mobile terminal is located in the preset holding space based on the classifier and according to a state sample of the target mobile terminal, wherein sending the classifier to the target mobile terminal comprises: performing a format conversion on the classifier, to enable the classifier to be suitable to an operation environment of the target mobile terminal; and sending the converted classifier to the target mobile terminal, performing a format conversion on the classifier, to enable the classifier to be suitable to an operation environment of the target mobile terminal; and sending the converted classifier to the target mobile terminal, characterized in that performing the format conversion on the classifier comprises: converting a binary file of the classifier in a spark format into a pmml file of the classifier in a pmml format. <EOS>