Logistic regression Maximum Likelihood in rapidminer
I wanted to get the maximum likelihood in logistic regression with this result (I'm really not sure if this is how it looks like):
I am currently using logistic regression to National Achievement Test(a performance exam for students,NAT -GRADE-REMARKS the Y axis) and their scholastic grade(In the example below ARTS-G12(Grade 12)-Q1(Quarter 1), the x Axis).
I wanted to know the maximum likelihood of students to Pass the National Achievement Test or to get VLM or LM. For my example in the image above the category in the National Achievement Test is VLM(Very Low Mastery) which is set to 1 and the LM(Low Master) Set to 0. VLM and LM are the only categories the student gets.
I wanted to know the maximum likelihood in this graph in order to fit a s like line in sigmoid function. I just really dont know how to interpret the scatterplot below. Do I need to zoom it out? I really cant interpret it
Regarding the interpretation of the scatterplot:
the obvious (for clarity): green is VLM, blue LM each dot means there is X number of students with the given grade on the horizontal axis. the coloring most probably defines X. Guess: the darker it gets the more students with the same grade?
From this graph, it seems a student's grade is not related to a VLM or VL category because there are low and high marks in both categories.
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