This Repository Contains R-Codes executed on various Datasets in RStudio. I Hope This Repository is very helpful for those who are Willing to build their Career in Data Science, Big Data.

Recursive Partitioning for Structural Equation Models

This is an initiative to help understand Statistical methods and Machine learning in a naive manner. You will find scripts, and theoretical contents required to clarify concepts, especially for bio-informatic students.

That's a project of machine learning, made in order to determine possible numbers to win a lottery (not finished yet).

Protests and agitations have long used as means for showing dissident towards social, political and economic issues in civil societies. In recent years we have witnessed a large number of protests across various geographies. Not to be left behind by similar trends in the rest of the world, South Africa, in recent years have witnessed a large num…

🌴↔️💊 Easy, robust forward simulating decision trees, calculating cost-effectiveness and PSA.

🌳🌳 Lightweight cost-effectiveness analysis using decision trees.

Through this research, we are able to model a student’s final grade in a particular subject and link it directly to certain relevant features that influence the outcome. We use the C5.0 decision tree technique to model the data.

Shiny App: Calculation of Age-dependent Reference Intervals (AdRI)

This module allows users to analyze k-means & hierarchical clustering, and visualize results of Principal Component, Correspondence Analysis, Discriminant analysis, Decision tree, Multidimensional scaling, Multiple Factor Analysis, Machine learning, and Prophet analysis.

HR Analytics in R Script: "Why Employees leave the company?"

Collection of R files consisting of predictive models built using various machine learning algorithms such as Decision Trees, Random Forests, Naive Bayes, etc

A simple R package for growing and plotting decision trees.

Application of Decision Tree C5.0, Random Forest, K-NN, Artificial Neural Network, Naive-Bayes algorithms in a Project using R

Mushrooms edibility classification

Research is mainly focus to predict and identify the Terrorist or Perpetrator, To do this, we use an existing data set and apply different Classification Techniques to analyze and interpret the factors that affect our model. For this we use Decision Tree, regression model and Random forest classification.

Projects who cover topics from text mining up to classification, association, clustering and regression algorithms

This R file has various Machine Learning models(Decision Tree, Random Forest, Logistic Regression) to classification the loan application to eligible for loan or not

This repository is about the source codes of an explainable algorithm for detecting drug-induced QT-prolongation at risk of torsades de pointes (TdP) regardless of heart rate and T-wave morphology, its comparison with a rule-based decision tree model and the data analysis underpinning the findings reported in the preprint paper submitted to the …