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training set

pl: training sets

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algorithm machine learning model data dataset parameter weight bias overfitting underfitting generalization epoch iteration batch gradient optimization loss function accuracy precision recall cross validation supervision label feature vector tensor matrix neural network deep learning regression classification clustering inference prediction sampling stochastic backpropagation activation function hyperparameter learning rate convergence regularization dropout normalization standardization outlier noise augmentation pattern recognition artificial intelligence heuristic probability statistics correlation variance mean median distribution entropy manifold dimension embedding centroid kernel perceptron layer node edge graph weighting tuning calibration evaluation metric performance error residual gradient descent

Last Updated: July 15, 2026•Report an Error

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