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10 results for “Metrics As Scores”
Trypanosoma Epitope Dataset: Valid Epitopes and Randomly Generated Peptides with Biochemical Metrics and AI-Generated Scores
<p>This dataset contains information about valid linear B-Cell epitopes from the Trypanosoma genus, as well as randomly generated peptides. It includes biochemical metrics generated by the EpiBuilder-1.0 tool and scores generated by the BepiPred-3.0 software. The data was originally collected from the IEDB and UniProtKB platforms and has been processed and enhanced with these informations for researchers interested in understanding the molecular interactions between Trypanosoma protozoans and the immune system.</p>
Metrics As Scores Dataset: Price, Weight, and Other Properties of Over 1,200 Ideal-Cut and Best-Clarity Diamonds
<p>This dataset is a subset of the original diamonds dataset with more than 54,000 diamonds. It was reduced to only contain diamonds of the best cut (ideal) and clarity (IF). The group is now given by the colors from J (worst) to D (best). This dataset comes from the R-package ggplot2 (Wickham 2016). For each color, we can examine the following attributes (<strong>features</strong>) of each diamond:</p> <ul> <li><em>Carat</em>: Weight of the diamond</li> <li><em>Depth</em>: Total depth percentage</li> <li><em>Price</em>: Price in US dollars [discrete]</li> <li><em>Table</em>: Width of top of diamond relative to widest point</li> <li><em>X</em>: Length in mm</li> <li><em>Y</em>: Width in mm</li> <li><em>Z</em>: Depth in mm</li> </ul> <p>It has a total of 7 Colors (<strong>groups</strong>): <em>D</em>, <em>E</em>, <em>F</em>, <em>G</em>, <em>H</em>, <em>I</em>, and <em>J</em>. The best color is <em>D</em> and the worst color is <em>J</em>. This dataset was created to analyze whether there are differences between the colors.</p>
Metrics As Scores Dataset: Elisa Spectrophotometer Positive Samples
<p>The ELISA dataset contains data from a spectrophotometer that determined the optical density of positive control samples, from five different lots, across five different runs. This dataset was introduced by (Schmid 1991).</p> <p>This dataset has the following <strong>Features</strong>:</p> <ul> <li><em>Lot1</em>: The first lot</li> <li><em>Lot2</em>: The second lot</li> <li><em>Lot3</em>: The third lot</li> <li><em>Lot4</em>: The fourth lot</li> <li><em>Lot5</em>: The fifth lot</li> </ul> <p>It has a total of 5 <strong>Groups</strong>: <em>Run1</em>, <em>Run2</em>, <em>Run3</em>, <em>Run4</em>, and <em>Run5</em>.</p>
Metrics As Scores Dataset: The Iris Flower Data Set
<p>The Iris flower data set or Fisher’s Iris data set is a multivariate data set used and made famous by the British statistician and biologist Ronald Fisher. The dataset was introduced in his 1936 paper "The Use of Multiple Measurements in Taxonomic Problems" (Fisher 1936) as an example of linear discriminant analysis.</p> <p>This dataset has the following Features:</p> <ul> <li><em>Petal.Length</em>: Length of the petal</li> <li><em>Petal.Width</em>: Width of the petal</li> <li><em>Sepal.Length</em>: Length of the sepal</li> <li><em>Sepal.Width</em>: Width of the sepal</li> </ul> <p>It has a total of 3 <strong>Groups</strong>: <em>setosa</em>, <em>versicolor</em>, and <em>virginica</em>.</p>
Metrics As Scores Dataset: Metrics and Domains From the Qualitas.class Corpus
<p>This dataset was created by extracting software metrics data from the Qualitas.class corpus (Terra et al. 2013; Tempero et al. 2010). Therefore, the principal quantity type is Metric, and the context is given by a system’s Domain (e.g., "Game", "Middleware", etc.). Some metrics were obtained on program-level, while others are package- or method-level metrics. Most of the metrics in the corpus are of discrete/integral nature. The corpus holds 23 types of pre-computed software metrics for a total of 111 systems which are spread across eleven different domains.</p> <p>This dataset has the following discrete <strong>Features</strong> (Metrics):</p> <ul> <li>CA: Afferent Coupling</li> <li>CE: Efferent Coupling</li> <li>DIT: Depth of Inheritance Tree</li> <li>MLOC: Method Lines of Code</li> <li>NBD: Nested Block Depth</li> <li>NOC: Number of Classes</li> <li>NOF: Number of Attributes</li> <li>NOI: Number of Interfaces</li> <li>NOM: Number of Methods</li> <li>NOP: Number of Packages</li> <li>NORM: Number of Overridden Methods</li> <li>NSC: Number of Children</li> <li>NSF: Number of Static Attributes</li> <li>NSM: Number of Static Methods</li> <li>PAR: Number of Parameters</li> <li>TLOC: Total Lines of Code</li> <li>VG: McCabe Cyclomatic Complexity</li> <li>WMC: Weighted Methods per Class</li> </ul> <p>The following features are continuous:</p> <ul> <li>LCOM: Lack of Cohesion in Methods</li> <li>RMA: Abstractness</li> <li>RMD: Normalized Distance</li> <li>RMI: Instability</li> <li>SIX: Specialization Index</li> </ul> <p>It has a total of 11 <strong>Groups</strong> (Domains): 3D; Graphics; Media, Databases, Diagrams; Visualiz., Games, IDE, Middleware, Parsers; Generators, Progr. Language, SDK, Testing, and Tool.</p>
Text-fig. 7. Plot of discriminant scores (R1/R2) of individual M1 of Apodemus spp. from particular Pleistocene biozones superimposed onto a plot of variation ranges for the respective variables for the Recent Apodemus sample (based on the discrimination analysis of total set of characters, both metric and non-metric). in Genus Apodemus In The Pleistocene Of Central Europe: When Did The Extant Taxa Appear?
Text-fig. 7. Plot of discriminant scores (R1/R2) of individual M1 of Apodemus spp. from particular Pleistocene biozones superimposed onto a plot of variation ranges for the respective variables for the Recent Apodemus sample (based on the discrimination analysis of total set of characters, both metric and non-metric).
Text-fig. 6. Plot of discriminant scores (R1/R2) of individual m1 and M1 teeth of Apodemus spp. from particular Pleistocene biozones superimposed onto a plot of variation ranges for the respective variables for the Recent Apodemus sample (based on the discrimination analysis of metric variables of M1 and m1). in Genus Apodemus In The Pleistocene Of Central Europe: When Did The Extant Taxa Appear?
Text-fig. 6. Plot of discriminant scores (R1/R2) of individual m1 and M1 teeth of Apodemus spp. from particular Pleistocene biozones superimposed onto a plot of variation ranges for the respective variables for the Recent Apodemus sample (based on the discrimination analysis of metric variables of M1 and m1).
The Dayhoff Exchange Score: A new metric to quantify site saturation in amino acid datasets prior to phylogenetic analysis
Open the record for dataset details and reuse information.
Assessing Diet, Stress Scores, and Other Health Metrics in Healthy Northern California Adults
ClinicalTrials.gov study NCT07265648. IPD Sharing: NO. Countries: 1. Publications: 0.
M-Score: An Empirically Derived Software Modularity Metric
<p>Anonymous upload for paper titled: "M-Score: An Empirically Derived Software Modularity Metric"</p>
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