jester: Jester dataset
In hyper2: The Hyperdirichlet Distribution, Mark 2
jester R Documentation
Jester dataset
Description
A likelihood function for the Jester datasets
Usage
data(jester)
Details
Object jester is a likelihood function for the 91 jokes rated
by the first 150 respondents in file ‘jester_dataset_1_3.zip’,
taken from Goldberg et al. Object jester_maxp is the result of
running maxp(jester).
Objects jester and jester_maxp can be generated by running
script ‘inst/jester.Rmd’, which includes some further technical
documentation. This file takes about 10 minutes to run.
The dataset is interesting because it has been analysed by many workers,
including Goldberg, for patterns; here I assume that all the respondents
behave identically (but randomly). It is included here because it is a
very severe numerical challenge in the context of the hyper2
package. I am not convinced that maxjest is even close to the
true evaluate.
References
Eigentaste: A Constant Time Collaborative Filtering Algorithm. Ken
Goldberg, Theresa Roeder, Dhruv Gupta, and Chris
Perkins. Information Retrieval, 4(2), 133-151. July 2001.
Examples
data(jester)
# maxp(jester) # takes too long
loglik(indep(jester_maxp),jester)
hyper2 documentation built on Aug. 21, 2022, 1:05 a.m.
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| jester | R Documentation |
Jester dataset
Description
A likelihood function for the Jester datasets
Usage
data(jester)
Details
Object jester is a likelihood function for the 91 jokes rated
by the first 150 respondents in file ‘jester_dataset_1_3.zip’,
taken from Goldberg et al. Object jester_maxp is the result of
running maxp(jester).
Objects jester and jester_maxp can be generated by running
script ‘inst/jester.Rmd’, which includes some further technical
documentation. This file takes about 10 minutes to run.
The dataset is interesting because it has been analysed by many workers,
including Goldberg, for patterns; here I assume that all the respondents
behave identically (but randomly). It is included here because it is a
very severe numerical challenge in the context of the hyper2
package. I am not convinced that maxjest is even close to the
true evaluate.
References
Eigentaste: A Constant Time Collaborative Filtering Algorithm. Ken Goldberg, Theresa Roeder, Dhruv Gupta, and Chris Perkins. Information Retrieval, 4(2), 133-151. July 2001.
Examples
data(jester) # maxp(jester) # takes too long loglik(indep(jester_maxp),jester)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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