Here is some recent update: Any thoughts? I have collected a list of experiment result data. I put them into a table.
There are N rows corresponding to N data points. For i-th row, it contains data of the form y_i = f(a_i, b_i, c_i, d_i, e_i, f_i), where f is a possibly stochastic function, a, b, c, d, e, f are variables. Is there a way that I can visualize so many data in a better way? I can do a histogram of all the y_i's, showing the distribution of y_i's. That's what I can think of. But how about those a_i, b_i, c_i, d_i, e_i, and f_i's. Any idea of how to visualize them? I really want to do a good presentation. Also, any way of linking y_i and f(a_i, b_i, c_i, d_i, e_i, and f_i's) all together(both the inputs and outputs)? losemind wrote: > > Hi all, > > I am doing some experiment studies... > > It seems to me that with different combination of 5 parameters, the end > results ultimately converged to two scalars. That's to say, some > combinations of the 5 parameters lead to one end result and some other > combinations of the 5 parameters lead to the other end result (scalar). > > I am thinking of this is sort of something like clustering or binary > classification. > > If I could figure out what combinations of the 5 parameters lead to what > type of end result, in the future, I will be able to predict or classify > without doing the whole experiment, which is very time consuming... > > Could someone give me some recommendations about what might be the best > stats model for doing this? > > And what might be the best stats tool for such task, and are these tools > available in R? > > Thanks a lot! > > > -- View this message in context: http://www.nabble.com/clustering-and-data-mining...-tp18765630p19131351.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.