Complete step by step solution. Microsoft Excel is the required tool. This assignment involves ordering of software modules, based on the number of faults predicted by a software quality prediction model. The models to be used for this assignment are as follows: 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 models.
Compare the performances of MOM for both the linear regression models. Use Alberg Diagram and Peformance Curve for each Model using fit and test data sets.
Use tables to summarize the results of MOM. Also provide analysis of your summary in at least 200 words. 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 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 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 models. Compare the performances of MOM for both the linear regression models. Use Alberg Diagram and Peformance Curve for each Model using fit and test data sets. Use tables to summarize the results of MOM. Also provide analysis of your summary in at least 200 words.
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