All Categories (1-3 of 3)

1. 

   Modeling the Sea Level Changes in Guam

   2019-10-10 01:49:22 | Datasets | Contributor(s): Avnika Manaktala | doi:10.4231/0A0F-7A84

   This project works on understanding the different statistical models that are available to analyze and predict mean sea level changes in Guam.

   https://purr.purdue.edu/publications/3289

2. 

   Code and Dataset for TARP Detection Benchmarks

   2017-05-12 20:50:14 | Datasets | Contributor(s): Kelsie Larson, Mireille Boutin | doi:10.4231/R7ST7MVC

   The TARP method uses random projections, followed by threshold classifications, to construct receiver-operating characteristic curves and uncover underlying structure in the given data.

   https://purr.purdue.edu/publications/2449

3. 

   Simplicity of K-means versus deepness of Deep Learning. A Case of Unsupervised Feature Learning with Limited Data

   2015-09-30 20:07:55 | Datasets | Contributor(s): Murat Dundar, Qiang Kou, Baichuan Zhang, Yicheng He, Bartlomiej P. Rajwa | doi:10.4231/R7N58J9Z

   A study contrasting K-means-based unsupervised feature learning and deep learning techniques for small data sets with limited intra- as well as inter-class diversity

   https://purr.purdue.edu/publications/1988