TechMusings (BigData,Hadoop,Pig,Hive,DataScience,IoT,EAI,SOA,J2EE)

R Notebook-College and Rank This is an  R Markdown  Notebook. When you execute code within the notebook, the results appear beneath the code. Try executing this chunk by clicking the  Run  button within the chunk or by placing your cursor inside it and pressing  Ctrl+Shift+Enter . Hide ds<-read.csv( "collegedatainput.csv" ) head(ds) Rank College Branch 1 1 IITB CSE 2 3 IITB CSE 3 10 IITB CSE 4 20 IITB CSE 5 30 IITB CSE 6 40 IITB CSE Hide str(ds) 'data.frame': 47 obs. of 3 variables: $ Rank : int 1 3 10 20 30 40 50 260 270 280 ... $ College: Factor w/ 3 levels "IITB","IITD",..: 1 1 1 1 1 1 1 1 1 1 ... $ Branch : Factor w/ 3 levels "CSE","EEE","MECH": 1 1 1 1 1 1 1 2 2 2 ... Hide ds Rank College Branch 1 1 IITB CSE 2 3 IITB CSE 3 10 IITB CSE 4 20 IITB CSE 5 30 IITB CSE 6 40

Example R Notebook for ScoreCard Model One often receives mailers on pre-approved loan based on creditworthiness. When one applies for credit, often it’s approved, sometimes it isn’t... Have you ever wondered how exactly the decision to approve a loan is done?  Was the bank able to clearly articulate the rationale of their decision to decline? To ensure fairness and transparency, there are compliance rules which mandates Banks to have such a mechanism. The Federal Trade Commission (FTC), the nation’s(US) consumer protection agency, enforces the Equal Credit Opportunity Act (ECOA), which prohibits credit discrimination on the basis of race, color, religion, national origin, sex, marital status,age, or because you get public assistance. In BFS, often underwriter needs to decide the creditworthiness of an applicant. Among other things, a scorecard is typically in place and long been used. Now with data deluge and better processing power many Analytical models are also used.