Iris_ml_project/docs/model-info.md

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