Xu Cui

You can’t believe how much jargon there is in binary classification. Just remember the following diagram (from wiki).

accuracy = ( TP + TN ) / (P+N), i.e. correctly classified divided by the total
false discovery rate (FDR) = TP / (TP+FP), i.e. correctly classified as positive, divided by all cases classified as positive

ROC (Receiver operating characteristic) is simply the plot of sensitivity against 1-specificity

AUC is the area under the ROC curve

ROC curve is close to the diagonal line if the two categories are mixed and difficult to classify; it will be high if the two categories are fully separated. Here I plot ROC curve in three simulated data with different overlaps between the two categories to be classified.

What’s the meaning of AUC? wiki says:

The AUC is equal to the probability that a classifier will rank a randomly chosen positive instance higher than a randomly chosen negative one.

This is hard to understand.

A single classifier won’t produce a curve; it only produces a single point (i.e. a single value of sensitivity and specificity). For example, we have 100 people and we want to know their gender based their heights and weights.  If our classifier is “male if height larger than 1.7m”, then this classifier only produces a point.

A class of classifiers will produce a curve. Assume we have a class of classifier called “classify male/female based on height”. Then by changing the threshold we will achieve a curve (ROC).

Then there are many classes of classifiers. For example, we can have a class called “classify by weight”, or “classify by weight and height linearly”, or “classify by weight and height nonlinearly”, etc. It’s likely the ROC produced by class “classify by weight and height linearly” is higher than the ROC produced by “classify by height” and thus produces a larger value of AUC.

So AUC is a property of a class of classifier, not a single classifier. But what does it exactly mean? …

How to get a cert in the first place:

http://www.adobe.com/devnet/air/articles/signing_air_applications_print.html

If you encounter this error when signing your AIR application, do the following:

1. Download the Thawte Code Signing CA from www.thawte.com/roots
2. Extract the contents and find file “Thawte Code Signing CA.cer” in folder Thawte Roots\Thawte Code Signing\Code Signing CA\
3. Open “Internet Option” from control panel, click tab Content, then Certificate, then Intermediate Certification Authority. Then click on “Import certificate” button and import “Thawte Code Signing CA.cer”
4. Now go back to your original p12 certificate file. Double click and import your system (be sure to enter your password). Check the option “Mark this key as exportable”
5. After importing, go to Internet Options > Content > Certificates
6. Select your certificate and click export
7. Next
8. Yes, export the private key
9. Format: PKCS, (checked) Include all certificates in the… , (checked) Enable Strong protection, (unchecked) Delete the private key …
10. Next
11. Enter Password for the certificate
12. Next enter filename and export the file

It should be good.

Reference:

http://forums.adobe.com/thread/433530