House-Mortgage-Dataset-Analysis
Part-1 Exploratory Dataset Analysis Home Mortgage NY
- Loading and analyzing dataset
- Visualizing the dataset
- Building a classification model to decide which predictors are most important
- Calculating the accuracy of the model by plotting ROC curve
Part-2
The main aim of the project was to predict whether a mortgage application will be accepted or not. Dataset was extracted from AER package in R.
Steps involved:
--Data extraction and cleansing
--Outliers detection using QQ-Plot and box-plots
--Skewness detection using density plots
--Model fitting using GLM
--Model selection using forward and hybrid methods
--Choosing the best model using ANOVA
--Predicting the model accuracy
--Plotting the ROC curve
--Conclusion:
On the basis of various analysis performed; the most significant predictors are:
Payment to Income Ratio
Loan to value ratio
Credit history: consumer payments
Public bad credit record
Insurance
Ethnicity
Marital status