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We present a new solar wind origin classification scheme developed independently using unsupervised machine learning. The scheme deduces 3 types of solar wind; coronal hole wind, streamer belt wind, and'unclassified'which does not fit into either of the previous two categories. The classification scheme is created using 6 non-evolving solar wind parameters (eg, ion charge states and composition) measured during Ulysses' three fast latitude-scans. The scheme is subsequently applied to the whole of the Ulysses and ACE datasets. The scheme uses the oxygen charge state ratio, proton specific entropy, carbon charge state ratio, alpha-to-proton ratio, iron-to-oxygen ratio, and the mean iron charge state. Thus, the classification scheme is grounded in the properties of the solar source regions. Furthermore, the techniques used are selected specifically to reduce the introduction of subjective biases into the …