scipy.cluster.hierarchy.inconsistent¶

scipy.cluster.hierarchy.inconsistent(Z, d=2)[source]¶

Calculates inconsistency statistics on a linkage.

Note: This function behaves similarly to the MATLAB(TM) inconsistent function.

Parameters:

Parameters:	Z : ndarray The \((n-1)\) by 4 matrix encoding the linkage (hierarchical clustering). See `linkage` documentation for more information on its form. d : int, optional The number of links up to d levels below each non-singleton cluster.
Returns:	R : ndarray A \((n-1)\) by 5 matrix where the `i`‘th row contains the link statistics for the non-singleton cluster `i`. The link statistics are computed over the link heights for links \(d\) levels below the cluster `i`. `R[i,0]` and `R[i,1]` are the mean and standard deviation of the link heights, respectively; `R[i,2]` is the number of links included in the calculation; and `R[i,3]` is the inconsistency coefficient, \[\frac{\mathtt{Z[i,2]} - \mathtt{R[i,0]}} {R[i,1]}\]

Z : ndarray

The \((n-1)\) by 4 matrix encoding the linkage (hierarchical clustering). See linkage documentation for more information on its form.

d : int, optional

The number of links up to d levels below each non-singleton cluster.

Returns:

R : ndarray

A \((n-1)\) by 5 matrix where the i‘th row contains the link statistics for the non-singleton cluster i. The link statistics are computed over the link heights for links \(d\) levels below the cluster i. R[i,0] and R[i,1] are the mean and standard deviation of the link heights, respectively; R[i,2] is the number of links included in the calculation; and R[i,3] is the inconsistency coefficient,

\[\frac{\mathtt{Z[i,2]} - \mathtt{R[i,0]}} {R[i,1]}\]