I have done a dimensionality reduction of binary labelled data (0,1 labels) from 300 features to 2 features. The plot looks like -

enter image description here

What kind of inferences can I make from this plot? Can I infer -

  1. Linear models probably would not generalize well for this data?
  2. Non linear models would probably be a better fit for this data?
  3. For this feature space (300 features), the data is non-linear?
  4. What inferences can be made using PCA plots?

UPDATE: More context on the question. I am solving a classification problem (a model to predict class membership). I was doing exploratory data analysis to gauge if my data is better fit for linear or non-linear models. I know there are other ways to do this QQ-plots, feature-label scatter plots etc. But can we deduce this using a PCA plot as shown above? The original 300 features have 15 discrete features & 285 continuous features.

  • $\begingroup$ The questions are vague because you don't give enough details: what do you want to "model" or "fit"? Do you want a model to predict class membership? Apart from that, you seem to have some discrete features. Are all of them discrete? Only some of them? $\endgroup$ – amoeba Jan 27 '16 at 17:33
  • $\begingroup$ @amoeba amended the question to answer your clarifications. $\endgroup$ – Srikar Appalaraju Jan 28 '16 at 3:42

For your 4th question: I don't think you can conclude much from this plot beyond the fact that a two component reduction of your data doesn't seem to allow a good categorization.

For your 1st and 2nd: It still could be that, on your original 300 variable data set, linear models work well (or not), nonlinear models work well (or not).

For your 3rd: I don't understand. Data can't be linear or nonlinear - that's a characteristic of models, not data - and, since you've shown nothing about the full data set, you can't draw conclusions about it.

If you had found that the two components extracted 90% of the variance, then the above would have to be amended. But you haven't told us how well the PCA worked.

| cite | improve this answer | |

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.