IRIS-Flower-classification and Iris_Classification

These are **competitors** — both are standalone machine learning projects that independently implement iris flower classification using similar datasets and algorithms, serving the same educational purpose without functional integration between them.

Iris_Classification
20
Experimental
Maintenance 0/25
Adoption 9/25
Maturity 8/25
Community 24/25
Maintenance 0/25
Adoption 5/25
Maturity 9/25
Community 6/25
Stars: 84
Forks: 122
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stars: 13
Forks: 1
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
No License Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About IRIS-Flower-classification

amberkakkar01/IRIS-Flower-classification

This project is for the Identification of Iris flower species is presented

Implements multiple supervised learning algorithms (Decision Tree, K-Nearest Neighbors, SVM, and Logistic Regression) using scikit-learn to classify iris specimens. The project applies train-test-split methodology and evaluation metrics to benchmark classifier performance on the standard Iris dataset. Designed as an educational resource for machine learning beginners to understand algorithmic approaches and accuracy measurement.

About Iris_Classification

Ruban2205/Iris_Classification

This repository contains the Iris Classification Machine Learning Project. Which is a comprehensive exploration of machine learning techniques applied to the classification of iris flowers into different species based on their physical characteristics.

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