1. A modeling method for learning a task skill, which is performed by a learning engine having at least one processor, the modeling method comprising: receiving training data for a task to be performed by the learning engine; dividing, by the learning engine, the received training data into segments by using a geometric property of a predetermined probabilistic model; and learning, by the learning engine, a basis skill for the divided segments by modeling each divided segment; wherein said dividing of the received training data into segments includes: determining a segmentation point by analyzing geometric properties of a Gaussian mixture model (GMM) and a Gaussian mixture regression (GMR) for the received training data; and dividing the training data into segments based on the determined segmentation point.