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Machine Learning

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IDL Machine Learning Run machine learning applications on numerical data. Create and train models and apply them in classification, clustering, or regression applications.
IDL Machine Learning Routines Provides a list of routines used in machine learning.
IDLmlafArcTan Implements an arc tangent activation function.
IDLmlafBentIdentity Implements a bent identity activation function.
IDLmlafBinaryStep Implements a binary step activation function.
IDLmlafELU Implements an exponential linear unit activation function.
IDLmlafGaussian Implements a Gaussian activation function.
IDLmlafIdentity Implements an identity activation function.
IDLmlafISRLU Implements an inverse square root linear unit activation function.
IDLmlafISRU Implements an inverse square root unit activation function.
IDLmlafLogistic Implements a logistic activation function.
IDLmlafPReLU Implements a parametric rectified linear unit activation function.
IDLmlafReLU Implements a rectified linear unit activation function.
IDLmlafSinc Implements a sinc activation function.
IDLmlafSinusoid Implements a sinusoidal activation function.
IDLmlafSoftExponential Soft exponential activation function.
IDLmlafSoftmax Softmax activation function.
IDLmlafSoftPlus Soft plus activation function.
IDLmlafSoftSign Soft sign activation function.
IDLmlafTanH Hyperbolic Tangent activation function.
IDLmlAutoEncoder Implements an autoencoder model that can be used for clustering purposes.
IDLmlFeedForwardNeuralNetwork Implements a Neural Network model that can be used for classification purposes.
IDLmlKMeans Implements a K-means model that can be used for clustering purposes.
IDLmllfCrossEntropy Cross entropy loss function.
IDLmllfHuber Huber loss function.
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