# sanchita-hasure21/compositecementstrength_predictionmodel1 architecture

> Architecture diagram of the GitHub repository sanchita-hasure21/compositecementstrength_predictionmodel1, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-11-13). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/sanchita-hasure21/compositecementstrength_predictionmodel1
- Repository: https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1

## Overview

This repository is a concrete compressive-strength prediction pipeline. Its principal workflow loads the concrete dataset, engineers and scales features, splits training and test data, fits several regression models, and reports R² scores. `main.py` orchestrates these stages and prints the returned scores. The graph reflects the sampled source; it does not imply additional prediction-serving or persistence capabilities.

Main entry points: [`main.py`](https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/main.py) (Pipeline entry point), [`src/model_build.py`](https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/src/model_build.py) (Regression training and evaluation), [`src/data_ingestion.py`](https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/src/data_ingestion.py) (Data ingestion), [`src/data_preprocessing.py`](https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/src/data_preprocessing.py) (Feature preprocessing)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_workflow["Prediction workflow"]
  node_ingestion["Data ingestion<br/>[data_ingestion.py]"]
  node_preprocessing["Feature preprocessing"]
  node_main["Pipeline entry point<br/>[main.py]"]
end

subgraph group_modeling["Modeling and evaluation"]
  node_modeling["Regression training and evaluation<br/>[model_build.py]"]
end

subgraph group_inputs["Input data"]
  node_dataset["Concrete dataset<br/>[Concrete_Data.csv]"]
end

node_console(("Console output"))

node_ingestion -->|"reads"| node_dataset
node_main -->|"calls"| node_ingestion
node_main -->|"passes data"| node_preprocessing
node_main -->|"passes splits"| node_modeling
node_modeling -->|"returns scores"| node_main
node_modeling -->|"prints R²"| node_console
node_main -->|"prints scores"| node_console

click node_dataset "https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/data/Concrete_Data.csv"
click node_ingestion "https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/src/data_ingestion.py"
click node_preprocessing "https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/src/data_preprocessing.py"
click node_main "https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/main.py"
click node_modeling "https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/src/model_build.py"

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_ingestion,node_preprocessing,node_main toneBlue
class node_modeling toneAmber
class node_dataset toneMint
class node_console toneIndigo
```

## Components

### Prediction workflow

- [Data ingestion](https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/src/data_ingestion.py): `src/data_ingestion.py`
- [Feature preprocessing](https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/src/data_preprocessing.py): `src/data_preprocessing.py`
- [Pipeline entry point](https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/main.py): `main.py`

### Modeling and evaluation

- [Regression training and evaluation](https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/src/model_build.py): `src/model_build.py`

### Input data

- [Concrete dataset](https://github.com/sanchita-hasure21/compositecementstrength_predictionmodel1/blob/main/data/Concrete_Data.csv): `data/Concrete_Data.csv`

### Other components

- **Console output**

## Connections

- Data ingestion → Concrete dataset: reads (evidence: `src/data_ingestion.py`)
- Pipeline entry point → Data ingestion: calls (evidence: `main.py`)
- Pipeline entry point → Feature preprocessing: passes data (evidence: `main.py`)
- Pipeline entry point → Regression training and evaluation: passes splits (evidence: `main.py`)
- Regression training and evaluation → Pipeline entry point: returns scores (evidence: `main.py`)
- Regression training and evaluation → Console output: prints R² (evidence: `src/model_build.py`)
- Pipeline entry point → Console output: prints scores (evidence: `main.py`)