- Use the ensemble classification model to generate predictions for a given dataset.
- If your ensemble model consists of multiple individual models, then calculate the predictions of each individual model on same dataset.
- Calculate the classification metrics for each individual model's predictions. Examples of classification metrics are, Accuracy, Precision, Recall and F1-score.
- Use MATLAB functions 'var' and 'std' to calculate the Variance and Standard deviation respectively from the metrics obtained.
finding the standard deviation for a classification model
9 次查看(过去 30 天)
显示 更早的评论
how to find the standard deviation or variance of an ensemble classification model
0 个评论
回答(1 个)
Sandeep
2023-10-5
Hi Chandrima Debnath,
It is great to know that you are working with ensemble classification models. It is possible to calculate the standard deviation and variance of an ensemble classification model but it is important to identify appropriate Classification metrics to proceed.
You can use the following steps,
% MATLAB function to calculate Variance and Standard deviation using metrics
variance = var(metrics);
standardDeviation = std(metrics);
Hope you find it helpful.
0 个评论
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Classification 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!