Loader(obj[, behav, params, scope, ...])
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Loader refers to transformations which operate on Data Files. |
Imputer(obj[, params, scope, cache_loc, ...])
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This input object is used to specify imputation steps for a Pipeline. |
Scaler(obj[, params, scope, cache_loc])
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The Scaler piece refers to a piece in the Pipeline or ModelPipeline, which is responsible for performing any sort of scaling or transformation on the data which doesn't require the target variable, and doesn't change the number of data points or features. |
Sampler(obj[, ref_scope, params, cache_loc])
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The Sampler is a Pipeline or ModelPipeline piece that is used for operations which involve changing the number of subjects in just the training set. |
Transformer(obj[, params, scope, cache_loc])
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The Transformer is base optional component of the Pipeline or ModelPipeline classes. |
FeatSelector(obj[, params, scope, ...])
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The FeatSelector class is a base piece of ModelPipeline or Pipeline, which is designed to preform feature selection. |
Model(obj[, params, scope, param_search, ...])
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The Model class represents a base component of the Pipeline / ModelPipeline. |
Ensemble(obj, models[, params, scope, ...])
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The Ensemble object is a ModelPipeline (or Pipeline) piece, designed to be passed as an estimator, the same as Model. |
ParamSearch([search_type, cv, n_iter, ...])
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ParamSearch is special input object designed to be used with ModelPipeline or Pipeline that is used in order to define a hyperparameter search strategy. |