The Few_shot_learning_classifier
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 1. Introduction

The Few_shot_learning_classifier is an automatic classification system based on machine learning for amino acid, nucleoside monophosphate, saccharide and peptide nanopore events.

This code contains three parts as follows:
a. Import dataset.
b. Train Ensemble Classifier.
c. Make predictions with the returned "trainedClassifier" on predicting dataset.

 2. Operating procedures: 

-Unzip the Few_shot_learning_classifier.rar to local folder. 
-Open Few_shot_learning_classifier.m in MATLAB.
-Enter the file name of the training set in line 2. // example: Training Set.xlsx
-Enter the file name of the testing set in line 3. // example: Testing Set.xlsx
-Enter the file name of the predicting dataset in line 4. // example: Predicting Set.xlsx
-Run Few_shot_learning_classifier.m. The running time is about one minutes.

3. Output

a. The values of the variables "ValidationAccuracy" and "TestingAccuracy" are output in the command window.
b. The confusion matrix and scatter plot with predicted labels are output in the figure panel and saved as "output.jpg" in local folder.