tion">
    <p>This function allows to perform Kernel Learning Integrative Clustering on M
data sets relative to the same observations. The similarities between the
observations in each data set are summarised into M different kernels, that
are then fed into a kernel k-means clustering algorithm. The output is a
clustering of the observations that takes into account all the available data
types and a set of weights that sum up to one, indicating how much each data
set contributed to the kernel k-means cluste