This table should have the current status of known bugs. Please look
check here first before
contacting
me about a new one.
ID
|
Description
|
Release
|
Status
|
| 1 |
Call to eigs in Netlab function eigdec uses incorrect syntax. |
3.2 |
Fixed in 3.3
|
| 2 |
Call to sort in eigdec fails if complex eigenvalues are returned. |
3.2 |
Fixed in 3.3 |
| 3 |
gsamp can occasionally give errors if eigenvalues of covariance matrix are not positive reals. |
3.2 |
Fixed in 3.3 |
| 4 |
In the main help index there is a link to demkmean but the actual html file is demkmn1.
|
3.2 |
Fixed in 3.3 |
| 5 |
In gmminit the replacement of small entries in the covariance matrix (line 73) uses wrong index. |
3.2 |
Fixed in 3.3 |
| 6 |
In glmderiv gradient calculation does not work with a mask. |
3.2 |
Fixed in 3.3 |
| 7 |
In mlpfwd output calculation with softmax does not prevent overflow as in glmfwd. |
3.2 |
Fixed in 3.3 |
| 8 |
In gmm help text, some references are incorrect.
|
3.2 |
Fixed in 3.3 |
| 9 |
In gmmpost treatment of rows in which all activations are zero is deficient. Fixed version warns and sets all posteriors to equal values. |
3.2 |
Fixed in 3.3 |
| 10 |
In book canonical variates worked example, canvar did not normalise calculations of within and between class covariance.
|
Book |
Fixed 18/11/03
|
| 11 |
In glmtrain Bayesian priors were not taken account of. Fixed version uses correct version of linear regression for scalar alpha and direct pseudo-inverse of Hessian for logistic and softmax outputs.
|
3.2 |
Fixed in 3.3 |
| 12 |
In mlp functions from book direct connections worked example, actfn was used as a field instead of outfn. In addition, mlpbkp did not treat the case of multiple outputs correctly.
|
Book |
Fixed 05/02/04
|
| 13 |
In glminit test for correct network type was syntactically incorrect.
|
3.2 |
Fixed in 3.3 |
| 14 |
gperr did not compute e2 correctly when the prior was not uniform for all parameters.
|
3.2 |
Fixed in 3.3 |
| 15 |
gmmsamp did not sample correctly from a mixture of PPCA Gaussians.
|
3.2 |
Fixed in 3.3 |
| 16 |
Optimisation and training algorithms give a warning message when they terminate because the maximum allowed number of iterations has been reached. Now the word "Warning" has been removed.
|
3.2 |
Fixed in 3.3 |