This development release fixes bugs and introduces functions for Kmeans cluster analysis.
With the already existing bayes-train, bayes-query and the new kmeans-train and kmeans-query functions, newLISP now implements 2 of the most - or even the 2 most - used machine-learning algorithms as fast native functions.
Changes notes and files: http://www.newlisp.org/downloads/development/
Ps: Users of 10.5.0 who use the bigint functions system should also switch to v.10.5.2 (the fixes where already in v.10.5.1)
newLISP Development release 10.5.2
Re: newLISP Development release 10.5.2
Typo in release notes:
After Jave update 7u21, install directory names could not have spaces.
After Java update 7u21, install directory names could not have spaces.
Hans-Peter
Re: newLISP Development release 10.5.2
Thanks HPW, I wonder if anybody is planning to use the new kmeans-train and kmeans-query functions?
Re: newLISP Development release 10.5.2
Hello, Lutz.
For the manual of Maintenance Release.
line 6548
line 16387
Both seem to be used in the web, and in Wikipadia
http://en.wikipedia.org/wiki/Euclidean_distance
I don't know which common.
For the manual of Maintenance Release.
line 6548
line 6553<td>calculate distances to cluster centroids or other data points</td>
↓
<td>calculates distances to cluster centroids or other data points</td>
And<td>partion a data set into clusters</td>
↓
<td>partitions a data set into clusters</td>
iscrit-t calculates the Student's t statistic for a given probability
kmeans-query calculate distances to cluster centroids or other data points
kmeans-train partion a data set into clusters
crit-z calculates the normal distributed Z for a given probability
maybe.crit-t calculates the Student's t statistic for a given probability
crit-z calculates the normal distributed Z for a given probability
kmeans-query calculate distances to cluster centroids or other data points
kmeans-train partion a data set into clusters
line 16387
I think that "Eucledian distance" equals "Euclidean distance".syntax: (kmeans-query <em>list-data</em> <em>matix-data</em></h4>
↓
syntax: (kmeans-query <em>list-data</em> <em>matix-data</em>)</h4>
Both seem to be used in the web, and in Wikipadia
http://en.wikipedia.org/wiki/Euclidean_distance
I don't know which common.