To achieve optimal performance in your reports, you need to create an efficient semantic model that has fast running queries and measures. When you have a good foundation, you can improve the model further by analyzing the query plans and dependencies and then making changes to further optimize ...
T. Welling (2018), Measures of model performance based on the log accuracy ratio, Space Weather, 16(1), 69-88.Morley, S.K.; Brito, T.V.; Welling, D.T. Measures of Model Performance Based on the Log Accuracy Ratio. Space Weather 2018, 16, 69-88, doi:10.1002/2017SW001669. [...
Wazed, MA, Ahmed, S (2008) Multifactor productivity measurements model (MFPMM) as effectual performance measures in manufacturing. Aust J Basic Appl Sci 2: pp. 987-996Wazed, M.A., Ahmed, S. 2008. Multifactor Productivity Measurements Model (MFPMM) as Effectual Performance Measures in ...
Unifrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol. 2005; 71(12):8228–35. Article CAS Google Scholar Lozupone CA, Hamady M, Kelley ST, Knight R. Quantitative and qualitative β diversity measures lead to different insights into factors that ...
Quantify the value of machine learning for the business - Consider measures of how machine learning and automation will impact the business: How much will machine learning reduce costs? How many more users will be reached by increasing scale? How much time will the business save by being ...
This change is a step in the right direction toward optimizing the performance of a semantic model.The use of variables in your semantic model provides the following advantages:Improved performance - Variables can make measures more efficient because they remove the need for Power BI to evaluate ...
The robustness and statistical analysis of the ML algorithms (for example, Random Forest imparts over 0.99 F1-score for all five categories and p value \(\le\) 0.05 from Wilcoxon ranked test over accuracy measures) against varying training splits demonstrate the effectiveness of the proposed ...
return Results, the best model and its prediction on the objective of the human activity variables. 3.1.1. Support Vector Regression SVR [24,25] is an ML approach for regression problems, well established also for function approximation. There are several versions of this approach, but in this...
Not only mere evaluation results, but also additional information from students can improve prediction performed by ANNs. Thus, basic students’ information, along with cognitive and non-cognitive measures, were used to design predictive models of students’ performance by using three ANN models [58]...
(IVA), and Conners’ CPT (Rosvold, Mirsky, Sarason, Bransome, & Beck, 1956). These tests are often used for helping to support or rule out a diagnosis ofADHD. In addition there are some CPTs, such as the QbTest and Quotient, that combine attention andimpulsivitymeasures with motion ...