Matlab Tools Documentation
Type “HELP FILE_NAME” for all details.
Filename  Status 
Computes the kmer gapped kernel between the strings stored in S; 
final 
kmer_kernel.m 
final 
kmer_wildcard_kernel.m 
final 
bow_kernel.m This function computes the bag of words kernel matrix for the strings in S. The case of the letters is ignored. 
final 
bag_of_words.m function kernel=bag_of_words(s,t) This function computes the bag of words kernel between two strings 
(not optimal, just as example) 
centering.m Centers the matrix K 
final 
cholesky.m 

dualcca.m 

dualfisher.m 
final 
dualkmeans.m 

dualpca.m 

dualpls.m 
mmm 
normalise.m 
final 
pls.m 

simplenovelty.m 
final 
standardise.m 

visualise.m 

diag_red.m Based on Kandola et al SDP methods for diagonal reduction 
requires SEDUMI matlab toolbox 
rbf.m  
spectral_clustering.m
implementation of Ng, Weiss, Jordan methods 

svmnovelty.m Performs novelty detection based on a sample stored in K, for test samples specified in Ktest. Note that this is a naive version, simply making use of matlab’s builtin qpsolver. 
needs optimization toolbox 
svmctrain.m Computes the dual vector and the offset for support vector machine classification. Note that this is a naive version, simply making use of matlab’s builtin qpsolver. 
requires optim toolbox 
adjrand.m measure of “similarity” between two clusterings of the data 
final 
anova.m  
p_spectrum.m
computes the pspectrum kernel (dynamic programming) outputs the DP table 
purely for teaching purposes 
p_spectrum_bf.m (computes the pspectrum kernel by brute force) 
purely for teaching purposes 
p_spectrum_fast.m (dynamic programming faster implementation of p spectrum kernel) outputs the DP table 
purely for teaching purposes 
p_trie.m (p spectrum kernel again, based on tries) 
purely for teaching purposes 
blended_spectrum.m (blended spectrum up to p by dyn prog) outputs the DP table 
purely for teaching purposes 
blended_spectrum_bf.m (blended spectrum up to p by brute force) 
purely for teaching purposes 
blended_spectrum_fast.m (blended spectrum up to p – faster) outputs the DP table 
purely for teaching purposes 
subseq_count .m (same as discussed in book, for non continuous subsequences) outputs the DP table 
purely for teaching purposes 
ssk_fast.m (as in ch11, outputs the DP table) 
purely for teaching purposes 
WARNING: Do not use this software to control an aircraft or laser eye surgery. We cannot guarantee it is fully debugged.