This package contains codes of BP-MIP [1] and Diverse Density [2]. 
To implement BP-MIP-DD, just run Diverse Density firstly and uses the learned scales to re-scale attributes of the data set before presenting them to BP-MIP. 
To implement BP-MIP-PCA, just perform principle component analysis (PCA) (whose implementation is quite easy and left for the users) and present the projected data set to BP-MIP.

[1] Z.-H. Zhou, M.-L. Zhang. Neural networks for multi-instance learning. Technical Report, AI Lab, Computer Science & Technology Department, Nanjing University, Nanjing, China, Aug. 2002.
[2] Maron O. Learning from ambiguity [PhD dissertation]. Department of Electrical Engineering and Computer Science, MIT, 1998.