A collection of problems solved with machine learning algorithms, using R.

Classification on the Kobe Bryant Shot Selection dataset (https://www.kaggle.com/c/kobe-bryant-shot-selection/data) using Decision Trees

Multivariate Environmental Statistics (BEE6300) R Code

Performed segmentation analysis and predictive modeling on insurance broker performance to conclude a random forest model (highest AUC of 73%) predicted whether 2020 Gross Written Premium will increase or decrease from 2019 with a misclassification rate of 35%. Four classification models (classification trees, logistic regression, random forests…

Six machine learning models for predicting bladder cancer progression using Caret package

Material associated to the publication project on local trees methods for classification

Class projects

Classification of movie rankings

Lightcurve Classification for Periodically Varying Stars (SAMSI Undergraduate Workshop Project)

Projekty na przedmiot "Statystyka matematyczna i ekonomiczna" na II roku studiów inżynierskich na kierunku Informatyka i ekonometria na UR

Overview of DS, Classification Tree, Regression Tree, Logistic Regression, Multiple Linear Regression, Random Forest Classifiers, p-value approach to Decision Tree, Disease Progression Models, Neural Networks and Deep Learning.

This project has the aim to analyze the Heart Disease dataset to build a classifiers to predict whether people have heart disease or not.

factor selection, exploratory data analysis, statistical learning on both qualitative and quantitative data in R

This is a type of decision tree algorithm( C 5.0) popularly used in machine learning applied on credits dataset.

In May 2024, two friends and I analyzed the course descriptions of all Bachelor Degrees at Padua University. Our project had three phases: first, we scraped the data from the University’s websites; then we cleaned the data; and finally, we trained models to recognize each course's 'School' from its description.