Welcome to MVBLS’s documentation!

Multi-view broad learning systerm (MVBLS) [1] is a multi-view framework that bases on BLS [2]. It is designed to be efficient with the following advantages:

• Support of classification and regression in supervised multi-view or multi-modal learning.

• Support of classification and regression in semi-supervised multi-view or multi-modal learning [3].

• Support of two or more views or modals.

Contents:

• Python Quick Start
• Python API
• Parameters Tuning
• Python Examples

References

[1] Z. Shi, X. Chen, C. Zhao, H. He, V. Stuphorn and D. Wu, “Multi-view broad learning system for primate oculomotor decision decoding,” in IEEE Trans. on Neural Systems and Rehabilitation Engineering, vol. 28, no. 9, pp. 1908-1920, 2020.

[2] C. L. P. Chen and Z. Liu, “Broad learning system: An effective and efficient incremental learning system without the need for deep architecture,” in IEEE Trans. on Neural Networks and Learning Systems, vol. 29, no. 1, pp. 10-24, 2018.

[3] T. Qiu, X. Liu, X. Zhou, W. Qu, Z. Ning and C. L. P. Chen, “An adaptive social spammer detection model with semi-supervised broad learning,” in IEEE Trans. on Knowledge and Data Engineering, doi: 10.1109/TKDE.2020.3047857.

Indices and tables

• Index