finding the standard deviation for a classification model

8 visualizaciones (últimos 30 días)
Chandrima Debnath
Chandrima Debnath el 23 de Mayo de 2022
Respondida: Sandeep el 5 de Oct. de 2023
how to find the standard deviation or variance of an ensemble classification model

Respuestas (1)

Sandeep
Sandeep el 5 de Oct. de 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,
  1. Use the ensemble classification model to generate predictions for a given dataset.
  2. If your ensemble model consists of multiple individual models, then calculate the predictions of each individual model on same dataset.
  3. Calculate the classification metrics for each individual model's predictions. Examples of classification metrics are, Accuracy, Precision, Recall and F1-score.
  4. Use MATLAB functions 'var' and 'std' to calculate the Variance and Standard deviation respectively from the metrics obtained.
% MATLAB function to calculate Variance and Standard deviation using metrics
variance = var(metrics);
standardDeviation = std(metrics);
Hope you find it helpful.

Categorías

Más información sobre Classification en Help Center y File Exchange.

Etiquetas

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by