[BostonCard]

From reddit's /r/cfb page

https://www.reddit.com/r/CFB/comments/40...ency_2015/

I've had a blast doing this all season, and this is the final edition. Congratulations to Jeff Seidel for edging out Ken Medlin as the closest to average voter of the year. And of course, congratulations to Jon Wilner for edging out Sam McKewon as outlier in chief. It's been a wonderful season.

For those of you who have never seen a dendrogram, it is a measure of relatedness between individuals.  The higher up the branching point, the greater the differences in voting pattern; the lower the branching point, the more similar people are.  As the picture shows, there appear to be two main clusters of voters, and then three voters, including our dear old pal Wilner, who are outliers.

BC

[BostonCard]

From reddit's /r/cfb page

https://www.reddit.com/r/CFB/comments/40...ency_2015/

I've had a blast doing this all season, and this is the final edition. Congratulations to Jeff Seidel for edging out Ken Medlin as the closest to average voter of the year. And of course, congratulations to Jon Wilner for edging out Sam McKewon as outlier in chief. It's been a wonderful season.

For those of you who have never seen a dendrogram, it is a measure of relatedness between individuals.  The higher up the branching point, the greater the differences in voting pattern; the lower the branching point, the more similar people are.  As the picture shows, there appear to be two main clusters of voters, and then three voters, including our dear old pal Wilner, who are outliers.

BC

[Oasis]

Are the three on the left the ones who watch Stanford?

[Oasis]

Are the three on the left the ones who watch Stanford?

[FarmBoy]

I love that Wilner is an outlier. We need more voters outside the herd.

[FarmBoy]

I love that Wilner is an outlier. We need more voters outside the herd.

[Rally]

For those of us, few as we may be, who had "soft" majors, would you explain this a bit more.  Please type slowly.  I'm a slow reader.  Thanks.

[Rally]

For those of us, few as we may be, who had "soft" majors, would you explain this a bit more.  Please type slowly.  I'm a slow reader.  Thanks.

[Robbie]

For those of us, few as we may be, who had "soft" majors, would you explain this a bit more.  Please type slowly.  I'm a slow reader.  Thanks.

Take each voter's ranking each week as a vector. You calculate the distance between one vector and another using some standard technique (Jaccard distance, Euclidean, cosine similarity, ...). Sum the distances over the season to get a composite similarity between voters. You then pairwise combine voters based on minimum cumulative distance. Once combined you should use that pair's aggregate vectors for further comparison. Repeat this process until the group is unified. The sequence of combinations can be expressed as a tree as seen above.

sorry....

[Robbie]

For those of us, few as we may be, who had "soft" majors, would you explain this a bit more.  Please type slowly.  I'm a slow reader.  Thanks.

Take each voter's ranking each week as a vector. You calculate the distance between one vector and another using some standard technique (Jaccard distance, Euclidean, cosine similarity, ...). Sum the distances over the season to get a composite similarity between voters. You then pairwise combine voters based on minimum cumulative distance. Once combined you should use that pair's aggregate vectors for further comparison. Repeat this process until the group is unified. The sequence of combinations can be expressed as a tree as seen above.

sorry....

[Rally]

[quote author=ferrari link=topic=14387.msg152766#msg152766 date=1452743788]
For those of us, few as we may be, who had "soft" majors, would you explain this a bit more.  Please type slowly.  I'm a slow reader.  Thanks.

Take each voter's ranking each week as a vector. You calculate the distance between one vector and another using some standard technique (Jaccard distance, Euclidean, cosine similarity, ...). Sum the distances over the season to get a composite similarity between voters. You then pairwise combine voters based on minimum cumulative distance. Once combined you should use that pair's aggregate vectors for further comparison. Repeat this process until the group is unified. The sequence of combinations can be expressed as a tree as seen above.

sorry....
[/quote]

Oh yeah, duh!  What was I thinking?  I forgot to calculate Jaccard distance.  Humiliating.  Wanna arm wrestle?

[Rally]

[quote author=ferrari link=topic=14387.msg152766#msg152766 date=1452743788]
For those of us, few as we may be, who had "soft" majors, would you explain this a bit more.  Please type slowly.  I'm a slow reader.  Thanks.

Take each voter's ranking each week as a vector. You calculate the distance between one vector and another using some standard technique (Jaccard distance, Euclidean, cosine similarity, ...). Sum the distances over the season to get a composite similarity between voters. You then pairwise combine voters based on minimum cumulative distance. Once combined you should use that pair's aggregate vectors for further comparison. Repeat this process until the group is unified. The sequence of combinations can be expressed as a tree as seen above.

sorry....
[/quote]

Oh yeah, duh!  What was I thinking?  I forgot to calculate Jaccard distance.  Humiliating.  Wanna arm wrestle?