1. A method for building an adaptive soft sensor, comprising the following steps: operating an online subtractive cluster algorithm to divide online data into a plurality of local regions according to a schedule vector, using an input vector to construct an inferential model according to the local regions; converting the online subtractive cluster algorithm into a recursive regression algorithm; updating existing clusters, adding new clusters, or merging two nearest clusters according to a density function of the schedule vector based on the online subtractive cluster algorithm; operating the recursive regression algorithm to update a plurality of local models in real-time according to the inferential model of the local regions; and obtaining a predicted output value by weighting the local models to create the inferential model.