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Full-Text Articles in Physical Sciences and Mathematics
A Comparison Of Machine Learning Techniques For Taxonomic Classification Of Teeth From The Family Bovidae, Gregory J. Matthews, Juliet K. Brophy, Maxwell Luetkemeier, Hongie Gu, George K. Thiruvathukal
A Comparison Of Machine Learning Techniques For Taxonomic Classification Of Teeth From The Family Bovidae, Gregory J. Matthews, Juliet K. Brophy, Maxwell Luetkemeier, Hongie Gu, George K. Thiruvathukal
George K. Thiruvathukal
This study explores the performance of machine learning algorithms on the classification of fossil teeth in the Family Bovidae. Isolated bovid teeth are typically the most common fossils found in southern Africa and they often constitute the basis for paleoenvironmental reconstructions. Taxonomic identification of fossil bovid teeth, however, is often imprecise and subjective. Using modern teeth with known taxons, machine learning algorithms can be trained to classify fossils. Previous work by Brophy et al. [Quantitative morphological analysis of bovid teeth and implications for paleoenvironmental reconstruction of plovers lake, Gauteng Province, South Africa, J. Archaeol. Sci. 41 (2014), pp. …
An Analysis Of Accuracy Using Logistic Regression And Time Series, Edwin Baidoo, Jennifer L. Priestley
An Analysis Of Accuracy Using Logistic Regression And Time Series, Edwin Baidoo, Jennifer L. Priestley
Jennifer L. Priestley
This paper analyzes the accuracy rates for logistic regression and time series models. It also examines a relatively new performance index that takes into consideration the business assumptions of credit markets. Although prior research has focused on evaluation metrics, such as AUC and Gini index, this new measure has a more intuitive interpretation for various managers and decision makers and can be applied to both Logistic and Time Series models.
Can Acute Dermal Systemic Toxicity Tests Be Replaced With Oral Tests? A Comparison Of Route-Specific Systemic Toxicity And Hazard Classifications Under The Globally Harmonized System Of Classification And Labelling Of Chemicals (Ghs), Nigel P. Moore, David J. Andrew, Donald L. Bjerke, Stuart Creton, David Dreher, Thomas Holmes, Pilar Prieto, Troy Seidle, Tim G. Rowan
Can Acute Dermal Systemic Toxicity Tests Be Replaced With Oral Tests? A Comparison Of Route-Specific Systemic Toxicity And Hazard Classifications Under The Globally Harmonized System Of Classification And Labelling Of Chemicals (Ghs), Nigel P. Moore, David J. Andrew, Donald L. Bjerke, Stuart Creton, David Dreher, Thomas Holmes, Pilar Prieto, Troy Seidle, Tim G. Rowan
Troy Seidle, PhD
Acute systemic toxicity data (LD50 values) and hazard classifications derived in the rat following oral administration and dermal application have been analysed to examine whether or not orally-derived hazard classification or LD50 values can be used to determine dermal hazard classification. Comparing the oral and dermal classifications for 335 substances derived from oral and dermal LD50 values respectively revealed 17% concordance, and indicated that 7% of substances would be classified less severely while 76% would be classified more severely if oral classifications were applied directly to the dermal route. In contrast, applying the oral LD50 values within the dermal classification …
Statistical Methods For Proteomic Biomarker Discovery Based On Feature Extraction Or Functional Modeling Approaches, Jeffrey S. Morris
Statistical Methods For Proteomic Biomarker Discovery Based On Feature Extraction Or Functional Modeling Approaches, Jeffrey S. Morris
Jeffrey S. Morris
In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational …
Assessment Of Model Development Techniques And Evaluation Methods For Binary Classification In The Credit Industry, Satish Nargundkar, Jennifer Priestley
Assessment Of Model Development Techniques And Evaluation Methods For Binary Classification In The Credit Industry, Satish Nargundkar, Jennifer Priestley
Jennifer L. Priestley
We examine and compare the most prevalent modeling techniques in the credit industry, Linear Discriminant Analysis, Logistic Analysis and the emerging technique of Neural Network modeling. K-S Tests and Classification Rates are typically used in the industry to measure the success in predictive classification. We examine those two methods and a third, ROC Curves, to determine if the method of evaluation has an influence on the perceived performance of the modeling technique. We found that each modeling technique has its own strengths, and a determination of the “best” depends upon the evaluation method utilized and the costs associated with misclassification.