Display and analyze ROC curves in R and S+
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Updated
Jul 28, 2024 - R
Display and analyze ROC curves in R and S+
Optimal cutpoints in R: determining and validating optimal cutpoints in binary classification
Evaluation of Binary Classifiers
Clustering validation with ROC Curves
Survival modelling using Cox proportional hazard regression model
A light and flexible R package to evaluate GWAS-based gene prioritization methods for complex traits.
Classification of spondylodiscitidis vs metastasis in the spine using multiple approaches in R
Complete package for all Data Science models using R. Starting form Preprocessing, Data Manipulation, Feature Engineering, Model Building, and Model Validation.
Data Science (Data preprocessing) along with machine learning where patients with digestive and kidney diseases are predicted using(kNN, Naïve Bayes , and Random Forest) classifiers in R Programming Language
ROC-GLM for DataSHIELD
Naive Bayes, Confusion Matrix, and ROC Analysis were conducted using R to determine how different variables lead to a customer of a bank taking out a personal bank loan.
Built a logistic regression model and a classification tree model for predicting the final status of a loan based on various variables available. Confusion matrix and misclassification rate for each model for a test dataset. Variables that appear to be important for predicting outcome. Plotted and described the ROC curves and AUC for the four mo…
R Shiny App to determine the factors that are most influential in patients’ survival of CHD. I created a Logistic Regression model in R using RStudio to predict the survival of CHD patients. Retrieved the data from the PHIS database using SQL & built tableau dashboards. The model predicted the survival of CHD with an AUC of over .90 and indicate…
R | Classification Project
Survival analysis in R for Public Health (Imperial College London through Coursera)
Hormone Therapy Decision Support System for Breast Cancer
Results of binary classification of Yelp reviews as pertaining to conventional or alternative medicine using random forests
You can find exercises and codes realized during this lecture
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