The intention of this study was to overview of a variety of performance metrics and approaches to their classification. The main goal of the study was to develop a typology that will help to improve our knowledge and understanding of metrics and facilitate their selection in machine learning ...
What are performance metrics in machine learning? Machine learning metrics help you quantify the performance of a machine learning model once it’s already trained. These figures give you an answer to the question, “Is my model doing well?” They help you do model testing right. Example of...
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We finally evaluated the durability of the Pt2CoCu and Pt/C cathodes from two metrics, voltage loss at 0.8 A cm–2and MA. After a standard ADT protocol of a square wave potential cycling between 0.60 and 0.95 V (3-second hold at each voltage) suggested by US DOE (Supplementar...
摘要原文 Informative benchmarks are crucial for optimizing the page segmentation step of an OCR system, frequently the performance limiting step for overall OCR system performance. We show that current evaluation scores are insufficient for diagnosing specific errors in page segmentation and fail to ide...
Machine learning models − now commonly developed to screen, diagnose, or predict health conditions − are evaluated with a variety of performance metrics. An important first step in assessing the practical utility of a model is to evaluate its average performance over an entire population of in...
To potentially further optimize imputation performance of gene expression across global populations, we built transcriptome prediction models using both linear and non-linear machine learning (ML) algorithms and evaluated their performance in comparison to EN. We trained models using genotype and blood ...
2029 Accesses 6 Citations 4 Altmetric Metrics details Abstract Prediction models are commonly used to estimate risk for cardiovascular diseases, to inform diagnosis and management. However, performance may vary substantially across relevant subgroups of the population. Here we investigated heterogeneity of ...
Metrics Abstract Controlling the precise atomic architecture of supported metals is central to optimizing their catalytic performance, as recently exemplified for nanostructured platinum and ruthenium systems in acetylene hydrochlorination, a key process for vinyl chloride production. This opens the possibility...
The PER, WER, and CER were also significantly better than chance (p < .001 for all metrics, two-sided Wilcoxon signed-rank test with 3-way Holm-Bonferonni Correction for multiple comparisons). Statistics compare n = 15 total pseudo-blocks. For PER: stat = 0, p = ...