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Iris Classification using Logistic Regression

This repository contains a simple machine learning project that demonstrates how to train and evaluate a Logistic Regression model using the Iris dataset from scikit-learn.

📌 Project Description

The project follows a complete basic machine learning pipeline:

  1. Import required libraries
  2. Load the Iris dataset
  3. Split the data into training and testing sets
  4. Standardize features
  5. Train a Logistic Regression model
  6. Evaluate the model using accuracy and a classification report

📊 Dataset

  • Name: Iris Dataset
  • Source: Built-in dataset from scikit-learn
  • Classes:
    • Setosa
    • Versicolor
    • Virginica
  • Features:
    • Sepal length
    • Sepal width
    • Petal length
    • Petal width

🛠️ Requirements

  • Python 3.x
  • scikit-learn

Install dependencies with:

pip install scikit-learn