mvpa2.algorithms.hyperalignment

Transformation of individual feature spaces into a common space

The Hyperalignment class in this module implements an algorithm published in Haxby et al., Neuron (2011) A common, high-dimensional model of the representational space in human ventral temporal cortex.

Functions

get_trained_mapper(ds, commonspace, mapper)	Trains a given mapper using dataset and commonspace and computes residuals if necessary.
mean_axis0(a)
mean_xy(x, y[, weights])

Classes

Hyperalignment(**kwargs)

Align the features across multiple datasets into a common feature space.