Linear Regression Model with M5 Method of Attribute Selection: FAULTS = - 0.0516 * NUMUORS + 0.0341 * NUMUANDS - 0.0027 * TOTOTORS - 0.0372 * VG + 0.2119 * NLOGIC + 0.0018 * LOC + 0.005 * ELOC - 0.3091
Linear Regression Model with Greedy Method of Attribute Selection:
FAULTS = - 0.0482 * NUMUORS + 0.0336 * NUMUANDS - 0.0021 * TOTOTORS - 0.0337 * VG + 0.2088 * NLOGIC + 0.0019 * LOC - 0.3255
Obtain the predictions for both the fit data set and the test data set using the above two models. Perform Module Order Modeling for both fit and test data sets using both regression modelsCompare the performances of MOM for both linear regression models. Use Alberg Diagram and Peformance Curve for each Model using fit and test data setsUse tables to summarize the results of MOM. Also provide analysis of your summary.