I am very new to drupal, so I already apologize if I ask something very simplistic...

I have a site where I would like to add a new block to the front page of the website. This block would show the companies newest available training's. I created the sub-pages of the training's.
My thought process was that I create the sub-pages, then create a new type of content (with the cck) where I can add the new sub-page node names and their links.
I created the new content type with two fields. field_offeringlink and field_offeringtext. Where the the text would be the actuall promotional text and the link directing to the sub-page.
After this I wanted to create a Block that I would place on the front page, showing these two fields.
I couldn't figure out this part...
So how do I make the bloody block show my fields?

OR

If you have a better idea for this whole shannanigan then I am welcome to ideas.

My goal:

Create a dynamic block on the front page, that shows all the latest training's. Under dynamic I mean, that we can add-remove the links from the admin/content menu.

Thanks in advance!


Question: Can I use an SVM for labeling data as more than one class
Answer: Just to add to what @Barmaley.exe said (+1), if you want probabilities, then use an algorithm that was designed for that purpose, such as the Relevance Vector Machine, Gaussian Process classifier or Kernel Logistic Regression (I like KLR and use it a lot, e.g. here which gives some benchmark results compared to SVM and Gaussian process classification etc.).  Platt scaling will give probability estimates, but they are not likely to be as good as those from a model designed to give a probabilistic output.

One of the ideas behind the SVM is that it is better to solve the problem directly, rather than solving a more general problem and simplifying the answer.  For instance if you are only interested in discrete yes/no classification, then it is better to try and infer the decision boundary directly, rather than estimate the posterior probability of class membership (a more general problem) and then threshold at 0.5 (the simplification step).  The reason for this is that model resources are not allocated to improve the performance of the model away from the decision boundary and the problem of estimating the parameters is simplified, and less data are likely to be required.  The SVM then is likely to do a good job of estimating the decision boundary (or p = 0.5 contour of the probability), but the raw output of the SVM will not necessarily be a good basis for estimating the probability away from the decision boundary.