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Similarly, the number of dimensions of a feeling can vary, as can the characteristics of each dimension. In machine learning and statistics, models without a fixed number of dimensions ("parameters") are represented with stochastic processes, like the Dirichlet process, the Chinese Restaurant process, and the Indian Buffet process, and they're studied as "nonparametric methods".