ID3 Decision Tree based on iris.data
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Updated
Oct 31, 2017 - Python
ID3 Decision Tree based on iris.data
This Repository contains the Iris Dataset Project created by using 4 different ML Algorithms.
Principle Component Analysis on IRIS data set
Here, I will put Machine learning tasks which are done using Automated Machine Learning.
Iris flower classification among setosa, verginica and versicolor.
A simple iris plant classifier built with React and Flask.
A machine learning project for classifying iris flowers into three species using sepal and petal characteristics. The repository includes EDA, advanced data visualization, and model evaluation, achieving 100% accuracy. Explore data, models, and visualizations in the notebook, images, and data folders.
Implementation of a multi-layered neural network that classifies iris flowers based on sepal length, sepal width, petal length, and petal width. The ANN is trained using the Iris dataset and the program prompts user input.
These are the tasks which I have performed during my Data Science Internship by Oasis Infobyte
Decision tree classifier on different dataset.
☘This repository contains a Python script for classifying the Iris dataset using the Random Forest algorithm.
Classification of IRIS Dataset using various distance metrics.
Iris Classification : Developed a ML Model for classifying iris flowers based on their features using Python, scikit-learn, and TensorFlow.
PyCaret: Simplifying machine learning workflows with a low-code, open-source Python library.
Python Application for an Iris Recognition System using OpenCV. The project aims to create a database system and iris analyzer for fast fast and accurate iris recognition.
Use sklearn's iris dataset to practice classfication
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