# tejsaxena-0811/tejsaxena_iris_dataset_ml architecture

> Architecture diagram of the GitHub repository tejsaxena-0811/tejsaxena_iris_dataset_ml, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-25). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/tejsaxena-0811/tejsaxena_iris_dataset_ml
- Repository: https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml

## Overview

This notebook project explores the Iris measurements and compares two species classifiers. The documented workflow covers exploratory visualization, feature/target preparation, an 80/20 split, Logistic Regression with five-fold cross-validation, and Random Forest; both models are evaluated, with a confusion-matrix heatmap specifically noted for Random Forest. The tree contains only the notebook, and no source excerpts were available, so relationships reflect README documentation rather than inspected implementation details.

Main entry points: [`Iris_Dataset.ipynb`](https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb) (Train/test split)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_exploration["Exploration"]
  node_eda["EDA visualizations<br/>[Iris_Dataset.ipynb]"]
end

subgraph group_modeling["Modeling"]
  node_prep["Feature preparation<br/>[Iris_Dataset.ipynb]"]
  node_split["Train/test split<br/>[Iris_Dataset.ipynb]"]
  node_logistic["Logistic Regression<br/>[Iris_Dataset.ipynb]"]
  node_forest["Random Forest<br/>[Iris_Dataset.ipynb]"]
end

subgraph group_evaluation["Evaluation"]
  node_log_eval["Logistic evaluation<br/>[Iris_Dataset.ipynb]"]
  node_forest_eval["Forest evaluation<br/>[Iris_Dataset.ipynb]"]
end

node_analyst(("Analyst"))
node_iris[("Iris dataset")]

node_analyst -->|"explores"| node_eda
node_iris -->|"visualizes"| node_eda
node_iris -->|"provides data"| node_prep
node_prep -->|"prepares features"| node_split
node_split -->|"trains"| node_logistic
node_split -->|"trains"| node_forest
node_logistic -->|"evaluates"| node_log_eval
node_forest -->|"evaluates"| node_forest_eval

click node_eda "https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb"
click node_prep "https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb"
click node_split "https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb"
click node_logistic "https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb"
click node_forest "https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb"
click node_log_eval "https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb"
click node_forest_eval "https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.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_eda toneBlue
class node_prep,node_split,node_logistic,node_forest,node_iris toneAmber
class node_log_eval,node_forest_eval toneMint
class node_analyst toneIndigo
```

## Components

### Exploration

- [EDA visualizations](https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb): `Iris_Dataset.ipynb`

### Modeling

- [Feature preparation](https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb): `Iris_Dataset.ipynb`
- [Train/test split](https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb): `Iris_Dataset.ipynb`
- [Logistic Regression](https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb): `Iris_Dataset.ipynb`
- [Random Forest](https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb): `Iris_Dataset.ipynb`

### Evaluation

- [Logistic evaluation](https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb): `Iris_Dataset.ipynb`
- [Forest evaluation](https://github.com/tejsaxena-0811/tejsaxena_iris_dataset_ml/blob/main/Iris_Dataset.ipynb): `Iris_Dataset.ipynb`

### Other components

- **Analyst**
- **Iris dataset**

## Connections

- Analyst → EDA visualizations: explores
- Iris dataset → EDA visualizations: visualizes
- Iris dataset → Feature preparation: provides data
- Feature preparation → Train/test split: prepares features
- Train/test split → Logistic Regression: trains
- Train/test split → Random Forest: trains
- Logistic Regression → Logistic evaluation: evaluates
- Random Forest → Forest evaluation: evaluates