Tags: Machine Learning

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

The Purdue University Research Repository (PURR) is a university core research facility provided by the Purdue University Libraries, the Office of the Executive Vice President for Research and Partnerships, and Information Technology at Purdue (ITaP).