Index Catalog // ScholarsArchive@OSU

Creator:: Ahmed, Nahian and Hutchinson, Rebecca A.
Abstract:: A variety of important machine learning applications require predictions on test data with different characteristics than the data on which a model was trained and validated. In particular, test data may have a different relative frequency of positives and negatives (i.e., class distribution) and/or different mislabeling costs of false positive...
Resource Type:: Technical Report
Full Text:: require predictions on test data with different characteristics than the data on which a model was trained

Creator:: Mannan, Umme Ayda
Abstract:: Software entropy impacts the overall quality of software systems. High entropy hinders developers from understanding the purpose of a piece of code and can cause developers to make sub-optimal changes and introduce bugs. Researchers have used entropy scores to measure the naturalness of code. However, thus far, no one has...
Resource Type:: Technical Report
Full Text:: our data is time-series data. The paper is structured as follows, Section 2 presents our method

Creator:: Dayger Forbes, Catherine Anne
Abstract:: Resource availability follows seasonal cycles in environmental conditions. To align physiology and behavior with prevailing environmental conditions, seasonal animals integrate cues from the environment with their internal state. One of the systems animals use to integrate those cues is the hypothalamus-pituitary-adrenal (HPA) axis and its primary effector, glucocorticoid hormones. The...
Resource Type:: Dissertation

Creator:: Harry, George Yost, 1919-
Abstract:: The objective of the thesis is to present data upon which the management of the Oregon otter-trawl fishery can be based. In addition, a history of the Oregon trawl fishery is presented. A summary of gear development by many of the vessels in the Oregon fleet is presented in table...
Resource Type:: Dissertation
Full Text:: The objective of the thesis is to present data upon which the management of the Oregon otter-trawl

Creator:: Dilhara, Malinda, Ketkar, Ameya, and Dig, Danny
Abstract:: Enabled by a rich ecosystem of Machine Learning (ML) libraries, programming using learned models, i.e., Software-2.0, has gained substantial adoption. However, we do not know what challenges developers encounter when they use ML libraries. With this knowledge gap, researchers miss opportunities to contribute to new research directions, tool builders do...
Resource Type:: Research Paper
Full Text:: smaller components. In Software 2.0: Engineers amass training data and simply feed it into an ML algorithm

ScholarsArchive@OSU