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ml-cross-validation
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Readme
Utility library to do cross validation with supervised classifiers.
Cross-validation methods:
A list of the mljs supervised classifiers is available here in the supervised learning section, but you could also use your own. Cross validations methods return a ConfusionMatrix (https://github.com/mljs/confusion-matrix) that can be used to calculate metrics on your classification result.
npm i -s ml-cross-validation
const crossValidation = require('ml-cross-validation');
const KNN = require('ml-knn');
const dataset = [[0, 0, 0], [0, 1, 1], [1, 1, 0], [2, 2, 2], [1, 2, 2], [2, 1, 2]];
const labels = [0, 0, 0, 1, 1, 1];
const confusionMatrix = crossValidation.leaveOneOut(KNN, dataSet, labels);
const accuracy = confusionMatrix.getAccuracy();
If you have a library that does not comply with the ML Classifier conventions, you can use can use a callback to perform the classification. The callback will take the train features and labels, and the test features. The callback shoud return the array of predicted labels.
const crossValidation = require('ml-cross-validation');
const KNN = require('ml-knn');
const dataset = [[0, 0, 0], [0, 1, 1], [1, 1, 0], [2, 2, 2], [1, 2, 2], [2, 1, 2]];
const labels = [0, 0, 0, 1, 1, 1];
const confusionMatrix = crossValidation.leaveOneOut(dataSet, labels, function(trainFeatures, trainLabels, testFeatures) {
const knn = new KNN(trainFeatures, trainLabels);
return knn.predict(testFeatures);
});
const accuracy = confusionMatrix.getAccuracy();
You can write your classification library so that it can be used with ml-cross-validation as described in here For that, your classification library must implement
train
method. The train
method is passed the data as a first argument and the labels as a second.predict
method. The predict
method is passed test data and should return a predicted label.class MyClassifier {
constructor(options) {
this.options = options;
}
train(data, labels) {
// Create your model
}
predict(testData) {
// Apply your model and return predicted label
return prediction;
}
}
FAQs
Cross validation utility for mljs classifiers
The npm package ml-cross-validation receives a total of 95 weekly downloads. As such, ml-cross-validation popularity was classified as not popular.
We found that ml-cross-validation demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 8 open source maintainers collaborating on the project.
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