I am looking at data from the London Data Store based on social characteristics between London boroughs.

Since there are only about 30 London boroughs, the data sets I am looking at are naturally very small. For example, I might be fitting regression/correlations to a plot of about 30 points.

1. What are appropriate ways to conduct classification on such small data sets, and why? 'Why' is important.

I was thinking of something like SVM, or Naive Bayes.

2. What are very inappropriate ways to conduct classification here?

I am looking at data from the London Data Store based on social characteristics between London boroughs.

Since there are only about 30 London boroughs, the data sets I am looking at are naturally very small. For example, I might be fitting regression/correlations to a plot of about 30 points.

1. What are appropriate ways to conduct classification on such small data sets, and why? 'Why' is important.

I was thinking of something like SVM, or Naive Bayes. Or regression if the data is continuous.

2. What are very inappropriate ways to conduct classification here?