Niranjan Dey's repositories
Analysis-of-Top-Billionaires-Data
A data analysis project scraping and analyzing data about top 500 billionaires of the past 10 years
An-Overview-of-Adaptive-Designs-in-Clinical-Trials
The desired allocation proportion is assigning more patients to better treatments.
An-Overview-of-PPAS-Sampling-Scheme
Probability Proportional to Aggregative Size sampling method with an example
An-Overview-of-The-Kruskal-Wallis-One-Way-ANOVA-Test-and-Multiple-Comparisons
A project Presentation of Nonparametric Methods under Prof. N V Krishna Chaitanya Yerroju
Analysis-of-Poliocases-using-R
Identified trend, seasonality and other time series analysis of Time Series of data on incidence of Polio using R.
Classical-analysis-of-time-series
Classical analysis of Time series data on the stock prices (high price) of ICICI bank
COMPARISON-OF-TESTING-PROCEDURES-FOR-ONE-MISSING-DATA-IN-RBD
Compared approximate test and two more accurate test procedures numerically using simulation. Compared the performances of approximate test and accurate test procedures.
Diabetes-Classification-with-R
Classification of diabetes patient using Linear & Quadratic Discriminant analysis, Logit, Random Forest, Support Vector Machine and KNN in R.
Loan-Default-Prediction
This project aims to provide a robust and accurate solution to the loan defaulting problem, helping financial institutions make more informed lending decisions and reduce their risk exposure.
Recommendation-Systems-Electronic-Dataset-from-Amazon
Popularity based systems for popular items which are in trend right now, Collaberative Filtering (Item-Item) is used for the above customer based on the purchase history of other customers in the website.
Regression-Analysis-on-Drinking-Data
Linear regression, VIF, Auto Correlation.
team-work-files-college
presentations and a note
Telco-Churn-Analysis
Predicting churn among US telecom customers using Logistic Regression, Random Forest, Support Vector Machine and XG Boost in Python. Hyperparameter tuning using Random Grid search CV. Finding features of importance.