scispace - formally typeset
Search or ask a question

Answers from top 4 papers

More filters
Papers (4)Insight
The computational results indicate that the SVM model performs better.
SVM achieves consistent and promising results.
The results of model testing showed that the SVM achieves good predictive performance.
Proceedings ArticleDOI
Minal Deshpande, Preeti Bajaj 
01 Dec 2016
16 Citations
Improved performance measure shows satisfactory results upon application of SVM.

Related Questions

How to determine SVM values?3 answersTo determine the values for Support Vector Machines (SVM), various approaches have been proposed in the literature. One approach is to search for hyperparameters that minimize the estimate of the generalization error. This can be done using different performance measures such as k-fold cross-validation, leave-one-out error, Vapnik's measure, and the regularized risk functional. Another approach is to use a two-step variable selection process, where the best variable subsets are first identified, and then a data-dependent criterion is used to determine the final subset. Additionally, an SVM regression-based algorithm has been proposed for filling in missing data, where the SVM regression is used to predict the missing attribute values. Finally, a methodology for selecting hyperparameters directly from the training data has been advocated, which has shown good generalization performance in regression problems.
How can I interpret the results from the tables and graphs?5 answersTo interpret the results from tables and graphs in clinical research articles, it is important to ensure that tables present complete and clear access to data, while figures should be used to reveal interesting points in the article. Univariate regression and multivariate regression are commonly used methods to identify associations between exposure and outcomes in clinical research, but they can be difficult to interpret and may be associated with hidden biases. Tests of significance, such as those used in statistical analysis, can also cause difficulty in interpretation. In educational research, cognitive tools, such as concept mapping tools, can be used to assist learners in interpreting graphs and tables, reducing cognitive load and helping learners visually organize knowledge.
How to interpret research data?5 answersData interpretation involves several steps. First, researchers need to consider the purpose of the analysis and the questions they want to answer. They also need to determine the type of data needed and available for analysis. Once the data is collected, it needs to be organized and prepared for analysis. This involves arranging the data in an organized manner and providing a proper description. Next, researchers can start analyzing the data by identifying patterns, themes, and relationships. This systematic analysis allows for the development of explanations and interpretations based on the theory used in the research. For quantitative data, statistical analysis can be used to measure changes and predict consistency. In qualitative research, the analysis may involve exploring the application of a theory or model in a different context or hoping for a theory or model to emerge from the data. Overall, data interpretation requires careful consideration of the research questions, data organization, and systematic analysis.
How do I make SVM more accurate?9 answers
How to build SVM model in R?7 answers
How to interpret odds ratio in R?10 answers