To build a Classification Tree Model using CHAID Technique which of the two - 0.02 and other 0.05 would you assign to alpha2 (Merging Critieria) and alpha4 (Splitting Criteria) parameters?

Just like the choice of placement of a bushy Bonsai shrub or a tall coconut tree in our garden depends on various parameters, so is the decision on the type of CHAID tree we want to construct. A number of factors like the type of variable, the number of variables, the categorisation level of each variable, the depth of analysis one wants to conduct, size of data set, etc, influences the choice of the merging and splitting criteria.

The higher the alpha2, the denser is our CHAID tree; higher the alpha4, the taller is our tree. The denser tree helps us analyse the impact of various categories of variables on target variables with microscopic accuracy. A taller tree portrays good picture of how the individual variables impact the target variable.

		Number of variables
		Less	More
Number of  categories	Less	alpha2 and  alpha4 = 0.05	alpha2 = 0.05, alpha4 = 0.02
	More	alpha2 = 0.02 alph4 = 0.05	alpha2 and  alpha4 = 0.02