# Model Information

## Overview

The Iris ML Predictor uses a machine learning model trained on the famous Iris dataset, which contains measurements of iris flowers from three different species:

1. Iris Setosa
2. Iris Versicolor
3. Iris Virginica

## Model Details

- **Model Type**: Classification model (likely a decision tree or random forest)
- **Features Used**:
  - Sepal Length (cm)
  - Sepal Width (cm)
  - Petal Length (cm)
  - Petal Width (cm)
- **Output**: Predicted Iris species
- **Model File**: `model.pkl`

## Dataset

The Iris dataset is a classic dataset in machine learning and statistics. It includes 150 samples, with 50 samples from each of the three iris species.

## Performance

The model has been trained and evaluated on the Iris dataset, with typical accuracy metrics exceeding 95% on test data.

## Limitations

- The model is only applicable to iris flowers of the three species in the training data
- Measurements must be provided in centimeters
- Extreme outlier values may lead to unreliable predictions