All functions |
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Chicago Ridership Data |
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Laplace correction parameter |
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Activation functions between network layers |
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Parameter to determine which neighbors to use |
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Parameters for possible engine parameters for C5.0 |
Support vector machine parameters |
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Parameters for possible engine parameters for Cubist |
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Degrees of freedom (integer) |
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Parameters for exponents |
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Minkowski distance parameter |
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Neural network parameters |
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Parameters for possible engine parameters for earth models |
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Functions to finalize data-specific parameter ranges |
Near-zero variance parameters |
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Space-filling parameter grids |
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Create grids of tuning parameters |
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Learning rate |
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Word frequencies for removal |
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Maximum number of retained tokens |
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Parameter for the effective minimum distance between embedded points |
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Number of unique values for pre-processing |
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Mixture of penalization terms |
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Number of randomly sampled predictors |
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Number of neighbors |
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Tools for creating new parameter objects |
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Number of cut-points for binning |
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Number of new features |
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Parameter to determine number of tokens in ngram |
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Parameters for class-imbalance sampling |
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Information on tuning parameters within an object |
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Amount of regularization/penalization |
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Proportion of predictors |
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MARS pruning methods |
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Return a dials parameter object associated with parameters |
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Parameters for possible engine parameters for randomForest |
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Tools for working with parameter ranges |
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Parameters for possible engine parameters for ranger |
Kernel parameters |
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Kernel Smoothness |
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Parametric distributions for censored data |
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Text hashing parameters |
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General thresholding parameter |
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Token types |
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Parameter functions related to tree- and rule-based models. |
Placeholder for unknown parameter values |
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Update a single parameter in a parameter set |
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Tools for working with parameter values |
Parameter for |
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Kernel functions for distance weighting |
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Term frequency weighting methods |
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Parameter for the moving window size |