Total Score 59 out of 60
DATA MINING ASSIGNMENT – WEEK 4 L. Hammond
Score 10 out of 10
1.
The two numeric attributes having the highest attribute significance scores are
“eight” with .65 and “eleven” with .82. Applying the hypothesis test for numerical significance, both attributes are significant predictors of class membership. ‘Eight” has a value of 8.36 and “eleven” has a value of 10.652.
Good work
Score 10 out of 10
2.
The correlation between the attributes has a value of 0.25467 and the scatterplot diagram does not depict a relationship between #colored vessels and thal. The elimination of one of these attributes is not supported. Good work
Score 10 out of 10
3.
The accuracy rates are equal, both at 61 %. The use of Quick Mine did not result in a poorer performing model. Good
Score 10 out of 10
4.
“Thal” as a function of “#colored vessels” resulted in an accuracy percentage of
19% and “chest pain type” as a function of “maximum heart rate” resulted in an accuracy percentage of 52%. “#colored vessels was not a good predictor of “that” nor was “maximum heart rate” a good predictor of “chest pain type”. This is a long and tedious approach to identifying redundancy among attributes. Good work
Score 10 out of 10
5.
a. Current stock price of $40 converted to a value between 1 and 0 is 0.667:
Good b. Given an output price value of 0.3, the predicted future stock price is
$29. Good
Score 9 out of 10
6.
Input to node i = 0.23 and input to node j = 0.06. Output to node i is evaluated as 1/1+(2.718) raised to the -.23 power and output to node j = 1/1+(2.718) raised to the -.06 power a. Input to node j =0.06, Input to node i =0.23 b. Output from node j

0.514995, Output from node i

0.442752

c. Input to node k

0.2728755, Output from node k

0.432201