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所在主题： K-Nearest Neighbor using JavaScript
文件名: knn-master.zip
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K-Nearest neighbor classifier A General purpose k-nearest neighbor classifier algorithm based on the k-d tree Javascript library develop by Ubilabs: k-d trees Methodsnew NaiveBayes() Constructor that takes no arguments. Example var knn = new KNN(); train(trainingSet, predictions) Train the Naive Bayes model to the given training set, predictions, and some options. Arguments trainingSet - A matrix of the training set. trainingLabels - An array of value for each case in the training set. options - Object with the options for the training. Options k - number of nearest neighbor (Default, number of label + 1). distance - distance function for the algorithm, the argument is a function, not an String (by default is euclidean, you can use the functions of this repository distance). Example var trainingSet = [[0, 0, 0], [0, 1, 1], [1, 1, 0], [2, 2, 2], [1, 2, 2], [2, 1, 2]];var predictions = [0, 0, 0, 1, 1, 1];knn.train(trainingSet, predictions); predict(dataset) Predict the values of the dataset. Arguments dataset - A matrix that contains the dataset. Example var dataset = [[0, 0, 0], [2, 2, 2]];var ans = knn.predict(dataset); export() Exports the actual K-Nearest Neighbor model to an Javascript Object. load(model) Returns a new K-Nearest Neighbor Classifier with the given model. Arguments model - Javascript Object generated from export() function. Authors Jefferson Hernandez License MIT [hide][/hide]
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