🌸 Iris Species Classification (Scikit-Learn)
A simple machine learning project that uses the classic Iris dataset from scikit-learn to classify flower species using supervised learning algorithms. The final model achieved an impressive 96% accuracy on the test data.
📌 Project Overview
This project demonstrates a complete ML workflow:
Loading the Iris dataset
Exploratory Data Analysis (EDA)
Preprocessing
Model training (Logistic Regression)
Model evaluation
Generating predictions
📊 Dataset
The Iris dataset contains:
150 samples
4 numeric features:
Sepal Length
Sepal Width
Petal Length
Petal Width
3 target classes:
Iris Setosa
Iris Versicolor
Iris Virginica
Dataset is loaded directly from sklearn.datasets.
🧠 Model Used
Algorithm: Logistic Regression Accuracy Score: 96%
📈 Results