Small data oversampling: improving small data prediction accuracy using the geometric SMOTE algorithm

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsIn the age of Big Data, many machine learning tasks in numerous industries are still restricted due to the use of small datasets. The limited availability of data often results in unsatisfactory prediction performance of supervised learning algorithms and, consequently, poor decision making. The current research work aims to mitigate the small dataset problem by artificial data generation in the pre-processing phase of the data analysis process. The oversampling technique Geometric SMOTE is applied to generate new training instances and enhance crisp data structures. Experimental results show a significant improvement on the prediction accuracy when compared with the use of original, small datasets and over other oversampling techniques such as Random Oversampling, SMOTE and Borderline SMOTE. These findings show that artificial data creation is a promising approach to overcome the problem of small data in classification tasks

Improving the quality of predictive models in small data GSDOT: A new algorithm for generating synthetic data

Douzas, G., Lechleitner, M., & Bacao, F. (2022). Improving the quality of predictive models in small data GSDOT: A new algorithm for generating synthetic data. PLoS ONE, 17(4), 1-15. [e0265626]. https://doi.org/10.1371/journal.pone.0265626In the age of the data deluge there are still many domains and applications restricted to the use of small datasets. The ability to harness these small datasets to solve problems through the use of supervised learning methods can have a significant impact in many important areas. The insufficient size of training data usually results in unsatisfactory performance of machine learning algorithms. The current research work aims to contribute to mitigate the small data problem through the creation of artificial instances, which are added to the training process. The proposed algorithm, Geometric Small Data Oversampling Technique, uses geometric regions around existing samples to generate new high quality instances. Experimental results show a significant improvement in accuracy when compared with the use of the initial small dataset as well as other popular artificial data generation techniques.publishersversionpublishe

The Grizzly, October 22, 2009

Big Brothers, Big Sisters: UC\u27s New Chapter • WVOU is Ursinus\u27 Hidden Treasure • Freelance Journalist Offers Students Advice • Ursinus Focuses on Pedestrian Safety, Adds More Lights to Main Street • USGA Meeting Talks Senior Halloween and New Clubs • Technology and its Role in College Student Recruitment • Dollar Store Bizarre Foods • Sophomore Week Celebration 2009 • Opinions: HPV Vaccine: One Less Reason for Some to Think That Protection is Necessary? • Men\u27s Basketball Comes Together for Another Great Season • UC Intramurals Give More Athletic Optionshttps://digitalcommons.ursinus.edu/grizzlynews/1796/thumbnail.jp

Scientific Reports / Microclimatic effects on alpine plant communities and flower-visitor interactions

High-alpine ecosystems are commonly assumed to be particularly endangered by climate warming. Recent research, however, suggests that the heterogeneous topography of alpine landscapes provide microclimatic niches for alpine plants (i.e. soil temperatures that support the establishment and reproduction of species). Whether the microclimatic heterogeneity also affects diversity or species interactions on higher trophic levels remains unknown. Here we show that variation in mean seasonal soil temperature within an alpine pasture is within the same range as in plots differing in nearly 500m in elevation. This pronounced heterogeneity of soil temperature among plots affected the spatial distribution of flowering plant species in our study area with a higher plant richness and cover in warmer plots. This increased plant productivity in warmer plots positively affected richness of flower visitor taxa as well as interaction frequency. Additionally, flower-visitor networks were more generalized in plots with higher plant cover. These results suggest that soil temperature directly affects plant diversity and productivity and indirectly affects network stability. The strong effect of heterogeneous soil temperature on plant communities and their interaction partners may also mitigate climate warming impacts by enabling plants to track their suitable temperature niches within a confined area.(VLID)471838

Interconnectedness of the Grinnellian and Eltonian niche in regional and local plant-pollinator communities

Understanding the causes and consequences of coexistence and thus biodiversity is one of the most fundamental endeavors of ecology, which has been addressed by studying species requirements and impacts conceptualized as their Grinnellian and Eltonian niches. However, different niche types have been mostly studied in isolation and thus potential covariation between them remains unknown. Here we quantified the realized Grinnellian niche (environmental requirements), the fundamental (morphological phenotype) and realized Eltonian niche (role in networks) of plant and pollinator taxa at a local and regional scale to investigate the interconnectedness of these niche types. We found a strong and scale-independent co-variation of niche types suggesting that taxa specialized in environmental factors are also specialized in their position in trait spaces and their role in bipartite networks. The integration of niche types thus will help to detect the true causes for species distributions, interaction networks, as well as the taxonomic and functional diversity of communities.(VLID)461537

Adjunctive homeopathic treatment of hospitalized COVID-19 patients (COVIHOM): A retrospective case series.

and purpose. COVID-19 is a novel viral disease causing worldwide pandemia. The aim of this study was to describe the effect of adjunctive individualized homeopathic treatment delivered to hospitalized patients with confirmed symptomatic SARS-CoV-2 infection. Thirteen patients with COVID-19 were admitted. Mean age was 73.4 ± 15.0 (SD) years. Twelve (92.3%) were speedily discharged without relevant sequelae after 14.4 ± 8.9 days. A single patient admitted in an advanced stage of septic disease died in hospital. A time-dependent improvement of relevant clinical symptoms was observed in the 12 surviving patients. Six (46.2%) were critically ill and treated in the intensive care unit (ICU). Mean stay at the ICU of the 5 surviving patients was 18.8 ± 6.8 days. In six patients (46.2%) gastrointestinal disorders accompanied COVID-19. The observations suggest that adjunctive homeopathic treatment may be helpful to treat patients with confirmed COVID-19 even in high - risk patients especially since there is no conventional treatment of COVID-19 available at present. [Abstract copyright: Copyright © 2021 Elsevier Ltd. All rights reserved.

Serum Leptin, Adiponectin and Tumor Necrosis Factor-α in Hyperlipidemic Rats with/without Concomitant Diabetes Mellitus

We compared the lipid profiles and serum levels of leptin, adiponectin and tumor necrosis factor-α (TNF-α) in rats with/without hyperlipidemia and with/without concomitant diabetes mellitus. Forty 10-wk-old male Wistar rats were divided into four groups. Groups A and C received standard food for 12 wks. Groups B and D received a high-fat diet enriched with 2% additional cholesterol. Moreover, insulin-deficient (type I) diabetes mellitus was induced in rats in groups C and D with intraperitoneal injections of streptozotocin. Fasting serum leptin levels were decreased in diabetic groups (groups C and D) compared with controls. Fasting serum adiponectin levels were decreased in groups C and D compared with group A. Serum TNF-α levels were augmented in groups B and D, those fed with an atherogenic diet. By contrast, TNF-α levels were decreased in group C. Our data suggest that serum leptin, adiponectin and TNF-α levels may serve as markers of obesity and type I diabetes mellitus