MVBLS 1.1

Multi-view Broad Learning Systerm

Multi-view Broad Learning Systerm (MVBLS)

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.

Get Started and Documentation

Our primary documentation is at https://mvbls.readthedocs.io/ and is generated from this repository. If you are new to MVBLS, follow the installation instructions on that site. The preferred way to install MVBLS is via pip from Pypi.

Next you may want to read:

• APIs & Parameters is an exhaustive list of customization you can make.
• Parameters Tuning is an exhaustive list of customization you can make.
• Examples showing command line usage of common tasks.

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.