Conditional Maximum-Entropy Training Tool
This tool enables training and testing of maximum-entropy models using a general-feature file format. The tool also supports RProp and GIS as training algorithms.
Discover an index of datasets, SDKs, APIs and open-source tools developed by Microsoft researchers and shared with the global academic community below. These experimental technologies—available through Azure AI Foundry Labs (opens in new tab)—offer a glimpse into the future of AI innovation.
This tool enables training and testing of maximum-entropy models using a general-feature file format. The tool also supports RProp and GIS as training algorithms.
MapCruncher lets users quickly convert existing maps into an online format that’s as fast and easy to use as Virtual Earth. PDF and raster maps can be converted in minutes just by clicking on corresponding…
Data sets for comparative study of parameter-estimation methods for statistical natural-language processing.
Source code and scripts for acoustic model training for phonetic classification.
A collection of short programs to compute standard information-retrieval performance measures—Recall, Precision, F-measure, Mean Average Precision, Mean Reciprocal Rank, Normalized Discounted Cumulative Gain—in the presence of tied scores.