# ramisrkit/car_evaluation_prediction architecture

> Architecture diagram of the GitHub repository ramisrkit/car_evaluation_prediction, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-11-10). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/ramisrkit/car_evaluation_prediction
- Repository: https://github.com/ramisrkit/car_evaluation_prediction

## Overview

This repository is a notebook-based car-acceptability classification project. Its documented workflow uses the categorical car dataset for preprocessing and train/test splitting, trains and tunes a Decision Tree, evaluates its performance, and supports predictions. PCA is a separate visualization path, not a model-training step. The notebook is not excerpted, so relationships below rely on README statements; the README also describes a saved model, but no such file appears in the repository tree.

Main entry points: [`Car_Evaluation_prediction.ipynb`](https://github.com/ramisrkit/car_evaluation_prediction/blob/main/Car_Evaluation_prediction.ipynb) (Encode and split), [`car_evaluation.csv`](https://github.com/ramisrkit/car_evaluation_prediction/blob/main/car_evaluation.csv) (Car evaluation data)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_data["Data preparation"]
  node_dataset[("Car evaluation data<br/>[car_evaluation.csv]")]
  node_preprocess["Encode and split"]
end

subgraph group_analysis["Analysis and modeling"]
  node_pca["PCA visualization"]
  node_tree["Decision Tree tuning"]
  node_evaluation["Performance evaluation"]
end

subgraph group_use["Model use"]
  node_prediction["Class prediction"]
end

node_user(("Project user"))

node_user -->|"runs notebook"| node_preprocess
node_dataset -->|"provides records"| node_preprocess
node_preprocess -->|"prepares visualization"| node_pca
node_preprocess -->|"provides training data"| node_tree
node_tree -->|"evaluated on split"| node_evaluation
node_user -->|"requests prediction"| node_prediction

click node_dataset "https://github.com/ramisrkit/car_evaluation_prediction/blob/main/car_evaluation.csv"
click node_preprocess "https://github.com/ramisrkit/car_evaluation_prediction/blob/main/Car_Evaluation_prediction.ipynb"
click node_pca "https://github.com/ramisrkit/car_evaluation_prediction/blob/main/Car_Evaluation_prediction.ipynb"
click node_tree "https://github.com/ramisrkit/car_evaluation_prediction/blob/main/Car_Evaluation_prediction.ipynb"
click node_evaluation "https://github.com/ramisrkit/car_evaluation_prediction/blob/main/Car_Evaluation_prediction.ipynb"
click node_prediction "https://github.com/ramisrkit/car_evaluation_prediction/blob/main/Car_Evaluation_prediction.ipynb"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_dataset,node_preprocess,node_user toneBlue
class node_pca,node_tree,node_evaluation toneAmber
class node_prediction toneMint
```

## Components

### Data preparation

- [Car evaluation data](https://github.com/ramisrkit/car_evaluation_prediction/blob/main/car_evaluation.csv): `car_evaluation.csv`
- [Encode and split](https://github.com/ramisrkit/car_evaluation_prediction/blob/main/Car_Evaluation_prediction.ipynb): `Car_Evaluation_prediction.ipynb`

### Analysis and modeling

- [PCA visualization](https://github.com/ramisrkit/car_evaluation_prediction/blob/main/Car_Evaluation_prediction.ipynb): `Car_Evaluation_prediction.ipynb`
- [Decision Tree tuning](https://github.com/ramisrkit/car_evaluation_prediction/blob/main/Car_Evaluation_prediction.ipynb): `Car_Evaluation_prediction.ipynb`
- [Performance evaluation](https://github.com/ramisrkit/car_evaluation_prediction/blob/main/Car_Evaluation_prediction.ipynb): `Car_Evaluation_prediction.ipynb`

### Model use

- [Class prediction](https://github.com/ramisrkit/car_evaluation_prediction/blob/main/Car_Evaluation_prediction.ipynb): `Car_Evaluation_prediction.ipynb`

### Other components

- **Project user**

## Connections

- Project user → Encode and split: runs notebook (evidence: `README.md`)
- Car evaluation data → Encode and split: provides records (evidence: `README.md`)
- Encode and split → PCA visualization: prepares visualization (evidence: `README.md`)
- Encode and split → Decision Tree tuning: provides training data (evidence: `README.md`)
- Decision Tree tuning → Performance evaluation: evaluated on split (evidence: `README.md`)
- Project user → Class prediction: requests prediction (evidence: `README.md`)