IncomLDL

WInLDL

class pyldl.algorithms.WInLDL(random_state: int | None = None)

WInLDL is proposed in paper [INCOM-LDL-LC24].

IncomLDL

class pyldl.algorithms.IncomLDL(random_state: int | None = None)

IncomLDL is proposed in paper [INCOM-LDL-XZ17].

References

[INCOM-LDL-LC24]

Xiang Li and Songcan Chen. No regularization is needed: efficient and effective incomplete label distribution learning. In Proceedings of the International Joint Conference on Artificial Intelligence, 4470–4478. 2024. URL: https://doi.org/10.24963/ijcai.2024/494.

[INCOM-LDL-XZ17]

Miao Xu and Zhi-Hua Zhou. Incomplete label distribution learning. In Proceedings of the International Joint Conference on Artificial Intelligence, 3175–3181. 2017. URL: https://doi.org/10.24963/ijcai.2017/443.

Further Reading

[INCOM-LDL-XSS+25]

Suping Xu, Lin Shang, Furao Shen, Xibei Yang, and Witold Pedrycz. Incomplete label distribution learning via label correlation decomposition. Information Fusion, 113:102600, 2025. URL: https://doi.org/10.1016/j.inffus.2024.102600.

[INCOM-LDL-ZTLH22]

Jing Zhang, Hong Tao, Tingjin Luo, and Chenping Hou. Safe incomplete label distribution learning. Pattern Recognition, 125:108518, 2022. URL: https://doi.org/10.1016/j.patcog.2021.108518.