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kshitizrohilla / iris-flower-classification-using-k-nearest-neighbor-algorithm

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This project uses the K-Nearest Neighbors (KNN) algorithm to classify Iris flowers based on their sepal and petal measurements. The dataset used in this project is the Iris Dataset, which includes 150 samples of Iris flowers, each with four features: sepal length, sepal width, petal length, and petal width.

knn k-nearest-neighbours iris-flowers iris-dataset knn-classification iris-flower-classification k-nearest-neighbor knn-model k-nearest-neighbors iris-classification knn-classifier iris-flower iris-flower-data knn-algorithm iris-flower-dataset iris-flower-category k-nearest-neighbor-classifier k-nearest-neighbors-algorithm
  • Updated May 7, 2023
  • Jupyter Notebook

yuvrajsaraogi / -Iris-Flower-Classification

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Iris flower has three species; setosa, versicolor, and virginica, which differs according to their measurements. Now assume that you have the measurements of the iris flowers according to their species, and the task is to train a machine learning model that can learn from the measurements of the iris species and classify them.

python nlp data-science data machine-learning natural-language-processing machine-learning-algorithms ml data-visualization classification data-analysis iris knn flower flower-classification knn-classification iris-flower-classification iris-classification iris-flower
  • Updated Mar 14, 2025
  • Jupyter Notebook

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