  Suppose the data consist of a set $S$ of points $x_j$, $1\leq j \leq J$,
distributed in a bounded domain $D\subset R^N$, where $N$ is a large number. An
algorithm is given for finding the sets $L_k$ of dimension $k\ll N$,
$k=1,2,...K$, in a neighborhood of which maximal amount of points $x_j\in S$
lie. The algorithm is different from PCA (principal component analysis)
