search for: interestingness

Hi, I am using Rattle 2.6.4 with R 2.12.2 on win64, is this a bug ? Following is the content after execute the associate analysis process: Summary of the Apriori Association Rules: Number of Rules: 23351 Summary of the Measures of Interestingness: support confidence lift Min. :0.1250 Min. :1 Min. :2.667 1st Qu.:0.1250 1st Qu.:1 1st Qu.:2.667 Median :0.1250 Median :1 Median :4.000 Mean :0.1314 Mean :1 Mean :3.983 3rd Qu.:0.1250 3rd Qu.:1 3rd Qu.:4.000 Max. :0.3750 Max. :1...

The scagnostics package implements the graph theoretic scagnostics described by Leland Wilkinson, Anushka Anand and Robert Grossman (http://www.ncdm.uic.edu/publications/files/proc-094.pdf), building on an old idea of Tukey's to define indices of "interestingness" to help guide the search for interesting features in the pair-wise scatterplots of a highly multivariate dataset. The scagnostics package currently only supports two methods, one which computes the scagnostics for a pair of variables, and the other for all pairs of variables in a data.frame....

...ow much more encouragement do you need? > One of the hardest things for traditional enterprise types to understand about Open Source is that the methodology seems to run counter to the notion that "everyone has his price." OS programmers tend to be more motivated by the intrinsic interestingness of a given piece of functionality than by someone else waving $$ in front of their eyes. This tendency seems verified by your complaint. Hopefully soon the wider capitalistic market will kick into gear, and the possibility of selling a lot of books will motivate people to write the documentat...

...) end else page.alert "Please upload an image file." end end end return end When I inspect the flickr object, I get the following: "#<Flickr:0xb5c2dfac @person_by_nsid={}, @test=nil, @shared_secret=\"\", @interestingness=nil, @reflection=nil, @photosets=nil, @api_key=\"\", @favorites=nil, @auth=nil, @caching=true, @client=#<XMLRPC::Client:0xb5c2de30 @http_header_extra=nil, @proxy_port=nil, @parser=nil, @proxy_host=nil, @host=\"www.flickr.com\", @create=nil, @auth=nil, @user=nil, @port=80, @us...

...# number of cases where x and y are both 0. (also D = length(x)-A-B-C) All the information is summarised in the 2-by-2 contingency table. Some years ago, Nathan Rountree and I supervised Yung-Sing Koh's data-mining PhD. She surveyed the data mining literature and found some 37 different "interestingness measures" for two-variable associations -- if I remember correctly; there were a lot of them. They fell into a much smaller number of qualitatively similar groups. At any rate, the Pearson correlation between x and y is (A*D - B*C)/sqrt((A+B)*(C+D)*(A+C)*(B+D)) So what happens when we delet...

...er of cases where x and y are both 0. (also D = length(x)-A-B-C) All the information is summarised in the 2-by-2 contingency table. Some years ago, Nathan Rountree and I supervised Yung-Sing Koh's data-mining PhD. She surveyed the data mining literature and found some 37 different "interestingness measures" for two-variable associations -- if I remember correctly; there were a lot of them. They fell into a much smaller number of qualitatively similar groups. At any rate, the Pearson correlation between x and y is (A*D - B*C)/sqrt((A+B)*(C+D)*(A+C)*(B+D)) So what happens when we...

...th(x)-A-B-C) > > > > All the information is summarised in the 2-by-2 contingency table. > > Some years ago, Nathan Rountree and I supervised Yung-Sing Koh's > > data-mining PhD. > > She surveyed the data mining literature and found some 37 different > > "interestingness measures" for two-variable associations -- if I > > remember correctly; there were a lot of them. They fell into a much > > smaller number of qualitatively similar groups. > > At any rate, the Pearson correlation between x and y is > > (A*D - B*C)/sqrt((A+B)*(C+D)*(A+...

...> > > > All the information is summarised in the 2-by-2 contingency table. > > Some years ago, Nathan Rountree and I supervised Yung-Sing Koh's > > data-mining PhD. > > She surveyed the data mining literature and found some 37 different > > "interestingness measures" for two-variable associations -- if I > > remember correctly; there were a lot of them. They fell into a much > > smaller number of qualitatively similar groups. > > At any rate, the Pearson correlation between x and y is > > (A*D - B*C)/sqrt((A+B)*(...

Let's go back to the original posting. > > > >> in each column, less than 10% values are 1, most of them are 0; > > > > > > > >> so I want to remove a row with value of zero in both columns when calculate correlation between two columns. > > So we're talking about correlations between binary variables. Suppose we have two 0-1-valued