1. An information processing apparatus that clusters an input data set, comprising: a memory having stored thereon (i) a plurality of reference data sets that were previously clustered, the plurality of reference data sets correspond to a plurality of reference images, and (ii) a first reference parameter for clustering a first reference data set of the plurality of reference data sets, the first reference data set of the plurality of reference data sets including a plurality of clusters corresponding to a region of a respective one of the plurality of reference images, the first reference parameter being a model parameter of mixture distribution, the first reference parameter corresponding to at least one of a number of clusters in the first reference data set, and a centroid of data points in each of the plurality of clusters; and at least one processor configured to execute computer readable instructions to, search the memory to obtain the first reference parameter of at least one of the plurality of reference data sets that is similar to the input data set, determine an initial value of the model parameter of mixture distribution of the input data set by combining (a) the first reference parameter of the first reference data set with (b) a second reference parameter of a second reference data set based on similarity between the input data set and the combined first and second reference data sets, at least one of the first reference parameter and the second reference parameter are obtained from the plurality of reference images, modify the initial value of the model parameter of mixture distribution of the input data set to match a probability density distribution of the input data set to generate an updated initial value, and cluster the probability density distribution of the input data set on a feature space of the input data set using the updated initial value of the model parameter of mixture distribution.