hypertools.reduce

hypertools.reduce(*args, **kwargs)[source]

Reduces dimensionality of an array, or list of arrays

Parameters:

x : Numpy array or list of arrays

Dimensionality reduction using PCA is performed on this array. If there are nans present in the data, the function will try to use PPCA to interpolate the missing values.

reduce : str or dict

Decomposition/manifold learning model to use. Models supported: PCA, IncrementalPCA, SparsePCA, MiniBatchSparsePCA, KernelPCA, FastICA, FactorAnalysis, TruncatedSVD, DictionaryLearning, MiniBatchDictionaryLearning, TSNE, Isomap, SpectralEmbedding, LocallyLinearEmbedding, and MDS. Can be passed as a string, but for finer control of the model parameters, pass as a dictionary, e.g. reduce={‘model’ : ‘PCA’, ‘params’ : {‘whiten’ : True}}. See scikit-learn specific model docs for details on parameters supported for each model.

ndims : int

Number of dimensions to reduce

Returns:

x_reduced : Numpy array or list of arrays

The reduced data with ndims dimensionality is returned. If the input is a list, a list is returned.