I have around 5000-6000 observations of nearly 8-10 variables (of which 2 are discrete, categorical) and a single numerical target parameter. As per initial evaluation, random forest regression might be a good algorithm for the current case.
Is the current observations/variables count adequate for the proposed method? If other regression algorithms are recommended as things are described currently, kindly let me know.