- 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
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how to find the standard deviation or variance of an ensemble classification model
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Answers (1)
Sandeep
on 5 Oct 2023
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.
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