hello friends community the metrics applying validation of clusters is obtained and the Davies Bouldin index negative returns me this is a bug? regards

excuse my ignorance , but I do not understand ???. In theory lei Davies Boulding index is a number greater than zero. How's that for optimization you mention? regards

i am searching for an explaxation to this negative mentioned davies-bouldin values. Please, can anyone explain to me why Rapidminer ist calculation negative values?

MartinLiebigAdministrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University ProfessorPosts: 3,517 RM Data Scientist

Hi Stefan,

i do not know why, but by default the values are multiplied by -1 so that you can run a minimizer on it. That's why the operator has an option called maximize with this description:

maximize

Description: This parameter specifies if the results should be maximized. If set to true, the result is not multiplied by minus one.

Simply check it and get what you like more

Best,

Martin

- Sr. Director Data Solutions, Altair RapidMiner - Dortmund, Germany

I read about the multiplication by -1. Thanks for the advanced paramrter advice. Now my values turn in positive ones. BUT, I am still wondering why the values are greater >1. Usualy Davies Boulding values are between 0 and 1 (0="good" clusters and 1="bad" clusters). Now that my values are greater 1, do you have a suggestions for interpretation?

Regards,

Stefan

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Options

MartinLiebigAdministrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University ProfessorPosts: 3,517 RM Data Scientist

So in either case, does the most optimal cluster according to DB index have the resulting DB that is farthest from zero, or closest? Or asked another way, for the absolute value of DB is a DB index of 10 better or worse than a DB index of 1?

0

Options

MartinLiebigAdministrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University ProfessorPosts: 3,517 RM Data Scientist

Hi,

as far as i know smaller absolute values are better. From the doc:

davies_bouldin: The algorithms that produce clusters with low intra-cluster distances (high intra-cluster similarity) and high inter-cluster distances (low inter-cluster similarity) will have a low Davies–Bouldin index, the clustering algorithm that produces a collection of clusters with the smallest Davies–Bouldin index is considered the best algorithm based on this criterion.

Best,

Martin

- Sr. Director Data Solutions, Altair RapidMiner - Dortmund, Germany

## Answers

537MavenIts just easier to use the negative value for optimization.

53Contributor IIIn theory lei Davies Boulding index is a number greater than zero.

How's that for optimization you mention?

regards

2Contributor IHey guys,

i am searching for an explaxation to this negative mentioned davies-bouldin values. Please, can anyone explain to me why Rapidminer ist calculation negative values?

My Performance Vectors are looking like this:

Performance Vector

Average within centroid distance

cluster_0: -1.831

cluster_1: -1.931

cluster_2: -1.856

cluster_3: -1.897

cluster_4: -1.903

cluster_5: -1.885

cluster_6: -1.891

cluster_7: -1.878

cluster_8: -1.818

cluster_9: -1.869

Davides Bouldin: -1.974

Thanks in advance for your help and reply,

Stefan

3,517RM Data ScientistHi Stefan,

i do not know why, but by default the values are multiplied by -1 so that you can run a minimizer on it. That's why the operator has an option called maximize with this description:

## maximize

Description: This parameter specifies if the results should be maximized. If set to true, the result is not multiplied by minus one.Simply check it and get what you like more

Best,

Martin

Dortmund, Germany

2Contributor IHey Martin,

thanks for your fast reply.

I read about the multiplication by -1. Thanks for the advanced paramrter advice. Now my values turn in positive ones. BUT, I am still wondering why the values are greater >1. Usualy Davies Boulding values are between 0 and 1 (0="good" clusters and 1="bad" clusters). Now that my values are greater 1, do you have a suggestions for interpretation?

Regards,

Stefan

3,517RM Data ScientistHi Stefan,

why do you think this should be normalized? According to Wikipedia: https://en.wikipedia.org/wiki/Davies%E2%80%93Bouldin_index i don't see any reason to have it in [0,1].

Nevertheless you can of course normalize the DB index.

~Martin

Dortmund, Germany

1Contributor ISo in either case, does the most optimal cluster according to DB index have the resulting DB that is farthest from zero, or closest? Or asked another way, for the absolute value of DB is a DB index of 10 better or worse than a DB index of 1?

3,517RM Data ScientistHi,

as far as i know smaller absolute values are better. From the doc:

Best,

Martin

Dortmund, Germany