Search Results for "cost sensitive"

Program described in the paper: MUMAL2: Improving sensitivity in shotgun proteomics using cost sensitive artificial neural networks and a threshold selector algorithm, 2016. By Fabio R. Cerqueira; Adilson M. Ricardo; Alcione P. Oliveira; Armin Graber; Christian Baumgartner.

Adaboost extensions for cost-sentive classification CSExtension 1 CSExtension 2 CSExtension 3 CSExtension 4 CSExtension 5 AdaCost Boost CostBoost Uboost CostUBoost AdaBoostM1 Implementation of all the listed algorithms of the cluster "cost-sensitive classification". They are the meta algorithms which requires base algorithms e.g. Decision Tree Moreover, Voting criteria is also required e.g. Minimum expected cost criteria Input also requires to load an arff file...

This project deals with a new concept of the heterogeneous grid for acceleration of the numerical linear algebra computing. We design this grid with respect to maximal ratio between cost and computational power. It allows a parallelization of scientific codes with minimal programming effort. We also optimize grid concept to be less sensitive to network parameters.

Developed at Medical Research Council UK to meet a common clinical trial need to track various types of clinical data. Users log dates of completed tasks against participant ID. Simple, useable, reduces lost data! Makes graphical progress reports.