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https://github.com/salihfurkaan/iris-flower-analysis
An analysis on Iris dataset of Scikit learn
https://github.com/salihfurkaan/iris-flower-analysis
data-science decision-trees iris-dataset linear-regression logistic-regression machine-learning machine-learning-algorithms scikitlearn-machine-learning support-vector-machines svm-classifier
Last synced: about 23 hours ago
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An analysis on Iris dataset of Scikit learn
- Host: GitHub
- URL: https://github.com/salihfurkaan/iris-flower-analysis
- Owner: salihfurkaan
- License: apache-2.0
- Created: 2024-05-05T21:44:50.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-05-09T09:53:19.000Z (6 months ago)
- Last Synced: 2024-05-09T10:59:41.227Z (6 months ago)
- Topics: data-science, decision-trees, iris-dataset, linear-regression, logistic-regression, machine-learning, machine-learning-algorithms, scikitlearn-machine-learning, support-vector-machines, svm-classifier
- Language: Jupyter Notebook
- Homepage:
- Size: 1.03 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Iris Flower Analysis and Machine Learning Models for Prediction
Click here to see the utilized dataset!
What is Iris?
Iris is a flowering plant genus of 310 accepted species with showy flowers. As well as being the scientific name, iris is also widely used as a common name for all Iris species, as well as some belonging to other closely related genera. A common name for some species is flags, while the plants of the subgenus Scorpiris are widely known as junos, particularly in horticulture. It is a popular garden flower.
In this project; Versicolor, Virginica and Setosa were used
![images](https://github.com/salihfurkaan/iris-flower-analysis/assets/119700956/1cf5c3b6-c259-4384-80fd-d60b9be50984)
Used Python Libraries
* Scikit-learn for cross validation, ML models, dataset and calculating mean squared error
* Pandas for converting arrays into data frames and some operations
* Matplotlib for data visualization
* Seaborn for data visualization
* Numpy for array-wise operations
Used Machine Learning Models
* Linear Regression
* Logistic Regression
* Decision Tree
* Support Vector Machines
* Random ForestPlots
![sepal_length_start](https://github.com/salihfurkaan/iris-flower-analysis/assets/119700956/7b1ba536-6915-4d33-af31-44d5cd8a7de2)
![petal](https://github.com/salihfurkaan/iris-flower-analysis/assets/119700956/3271bf95-fa41-4849-8009-08828d333176)
![lr](https://github.com/salihfurkaan/iris-flower-analysis/assets/119700956/bdfa399d-c0d3-4932-a5e0-abace0af6854)
![random_forest](https://github.com/salihfurkaan/iris-flower-analysis/assets/119700956/170931c0-bef2-4759-9e24-f2714fc789d4)![pp](https://github.com/salihfurkaan/iris-flower-analysis/assets/119700956/466a6f2c-5236-4202-a79f-b7ccea71ba8b)
![decision_tree](https://github.com/salihfurkaan/iris-flower-analysis/assets/119700956/009d7f62-36bc-4211-b066-3030d9666348)