# sakshi01coder/fake-product-review-detection architecture

> Architecture diagram of the GitHub repository sakshi01coder/fake-product-review-detection, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-26). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/sakshi01coder/fake-product-review-detection
- Repository: https://github.com/sakshi01coder/fake-product-review-detection

## Overview

This is a notebook-based fake product review classifier. Its documented user workflow accepts a review, preprocesses text with cleaning and TF-IDF, then predicts whether it is fake or genuine. A separate branch compares classifiers using standard metrics. The README describes labeled training data, while the tree also lists dataset.csv; without notebook excerpts, their exact wiring and implementation details cannot be verified.

Main entry points: [`A035,A044_MLA_Project .ipynb`](https://github.com/sakshi01coder/fake-product-review-detection/blob/main/A035%2CA044_MLA_Project%20.ipynb) (Review classifier), [`dataset.csv`](https://github.com/sakshi01coder/fake-product-review-detection/blob/main/dataset.csv) (Labeled reviews)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_workflow["Review workflow"]
  node_preprocess["Text preprocessing"]
  node_result["Fake or genuine"]
end

subgraph group_modeling["Modeling and evaluation"]
  node_predictor["Review classifier"]
  node_evaluation["Model evaluation"]
end

subgraph group_data["Review data"]
  node_dataset["Labeled reviews<br/>[dataset.csv]"]
end

node_user(("Review submitter"))

node_user -->|"submits review"| node_preprocess
node_preprocess -->|"transforms text"| node_predictor
node_predictor -->|"predicts label"| node_result
node_dataset -->|"training data"| node_predictor
node_predictor -->|"compared by"| node_evaluation

click node_preprocess "https://github.com/sakshi01coder/fake-product-review-detection/blob/main/A035%2CA044_MLA_Project%20.ipynb"
click node_predictor "https://github.com/sakshi01coder/fake-product-review-detection/blob/main/A035%2CA044_MLA_Project%20.ipynb"
click node_result "https://github.com/sakshi01coder/fake-product-review-detection/blob/main/A035%2CA044_MLA_Project%20.ipynb"
click node_evaluation "https://github.com/sakshi01coder/fake-product-review-detection/blob/main/A035%2CA044_MLA_Project%20.ipynb"
click node_dataset "https://github.com/sakshi01coder/fake-product-review-detection/blob/main/dataset.csv"

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_preprocess,node_result,node_user toneBlue
class node_predictor,node_evaluation toneAmber
class node_dataset toneMint
```

## Components

### Review workflow

- [Text preprocessing](https://github.com/sakshi01coder/fake-product-review-detection/blob/main/A035%2CA044_MLA_Project%20.ipynb): `A035,A044_MLA_Project .ipynb`
- [Fake or genuine](https://github.com/sakshi01coder/fake-product-review-detection/blob/main/A035%2CA044_MLA_Project%20.ipynb): `A035,A044_MLA_Project .ipynb`

### Modeling and evaluation

- [Review classifier](https://github.com/sakshi01coder/fake-product-review-detection/blob/main/A035%2CA044_MLA_Project%20.ipynb): `A035,A044_MLA_Project .ipynb`
- [Model evaluation](https://github.com/sakshi01coder/fake-product-review-detection/blob/main/A035%2CA044_MLA_Project%20.ipynb): `A035,A044_MLA_Project .ipynb`

### Review data

- [Labeled reviews](https://github.com/sakshi01coder/fake-product-review-detection/blob/main/dataset.csv): `dataset.csv`

### Other components

- **Review submitter**

## Connections

- Review submitter → Text preprocessing: submits review
- Text preprocessing → Review classifier: transforms text
- Review classifier → Fake or genuine: predicts label
- Labeled reviews → Review classifier: training data
- Review classifier → Model evaluation: compared by