MD (Data Mining & Modeling)

Overview

This repository contains data mining projects and practical assignments (Prácticas). It is structured as an R Project (MD.Rproj) and utilizes renv for reproducible dependency management.

Repository Structure

MD/
├── Practica_1/        # First practical assignment (deliverables, presentations, raw data descriptions)
├── Practica_2/        # Second practical assignment (tasks and documentation)
├── data/              # Raw, processed, and split datasets
├── src/               # R scripts and source code for data processing and analysis
├── markdown/          # RMarkdown files and notebooks
├── reports/           # Generated reports and project deliverables (e.g., D1, D3, D4)
├── slides/            # Presentations and slides used in class or for project defense
├── docs/              # Additional project documentation
├── teoria/            # Theoretical notes and course materials
├── misc/              # Miscellaneous files and temporary resources
├── renv/              # Local R environment library
├── renv.lock          # renv lockfile for dependency reproducibility
├── BeforeMissing.rds  # Intermediate dataset state (R data file)
└── Preprocessed_data.csv # Preprocessed dataset in CSV format

Directory Details

• Practica_1/ & Practica_2/: Contain the main assignment deliverables, including Word documents, Excel grids, and PowerPoint presentations outlining the analysis steps.
• data/: The primary data folder. Data analysis pipelines ingest data from this folder or the root directory (like Preprocessed_data.csv and BeforeMissing.rds) and output the processed models.
• src/ & markdown/: These directories contain the source code for the project. R scripts and RMarkdown models used for data processing, model training, and evaluation are organized here.
• reports/ & slides/: Contain formal reports, papers, and presentations generated during the course of the project.
• teoria/: Course theory and related study materials.

Setup & Execution

Prerequisites

• R and optionally RStudio
• The renv package installed in R.

Environment Setup

This project uses renv to maintain dependencies. To restore the exact package versions used in this project:

1. Open MD.Rproj in RStudio or launch R from the project root.
2. renv will automatically bootstrap itself using the .Rprofile.
3. Run the following command in the R console to restore the environment:

   renv::restore()

Disclaimer

Note that large data files and sensitive artifacts might be excluded via .gitignore. The files BeforeMissing.rds and Preprocessed_data.csv are tracked in the root for direct access during initial evaluation.