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Next, click on the white area below ``Enter next example.''
Then input your first labelled example *b*, *c(b)*. For example,
you may input 000111, 1. Note that comma is
essential. Then click Enter, and wait for the
response to be shown in the big area. After the respone has been displayed,
you may enter the next vector and the next label.

Adding both the vector and the label at the same time is just for
your *convenience*. The applet shows you what the algorithm *P*
has predicted on the current input vector *b*. If the prediction has
been correct, no new hypothesis is computed and thus not displayed.
If a prediction error occured, the applet is honestly telling you that, and
it displays its new hypothesis. Note that * negated*
variables are displayed by a

If you would like to run a new series, please hit the button ``RELOAD THIS APPLET.'' Enjoy!

Hopefully, now you have understood how the Wholist algorithm works
by trying it on some *small* examples. Did you find out how
many examples it takes in the best-case and
worst-case?

Then you may wonder how many examples are needed on average.

This finishes our introduction. We continue by explaining further
* learning models*. The next model is
Learning in the Limit.

This applet has been written by Olaf Trzebin and Thomas Zeugmann. Please report any bug you may find to

Thomas Zeugmann

- "thomas" at "ist.hokudai.ac.jp"