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Ways to improve data mining and management

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KTC
KTC's picture
Ways to improve data mining and management

See: http://www.kaggle.com/

Their motto:  We’re making data science a sport.

Also

http://www.kaggle.com/about

http://www.kaggle.com/prospect

What can we learn from this organiztaion?  How can they help us deal with ever-increasing amounts of data?

wel
wel's picture
Kaggle.com

Hi Tom,

Very interesting find! It would be interesting to see the regression of the number of Kaggle teams versus the reward value.

It is unclear how the AAVSO might engage this but the model bears consideration.

Cheers,

Doug

GJSa
Regression

I too was interested in the regression of no. of teams vs. reward. According to the website, 33 competitions have been completed so far with rewards ranging from 0 to $100k. Turns out the relationship between no. of teams and reward size isn't significantly different from zero. I've attached a plot. The gory statistical details are below.

Joel

 Call:

lm(formula = N_Teams ~ Reward, data = nonzero_finished)

Residuals:
Min 1Q Median 3Q Max
-180.53 -144.44 -92.89 44.37 762.35

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.013e+02 4.365e+01 4.610 6.54e-05 ***
Reward 1.279e-03 2.309e-03 0.554 0.584
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 225.7 on 31 degrees of freedom
Multiple R-squared: 0.0098, Adjusted R-squared: -0.02214
F-statistic: 0.3068 on 1 and 31 DF, p-value: 0.5836

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