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.

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📌 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

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📊 Dataset

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

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🛠️ Requirements

• Python 3.x
• scikit-learn

Install dependencies with:

pip install scikit-learn