This model predicts the class of the flower from the input data of sepal length, sepal width, petal length and petal width. The data used for training this model is from the iris dataset present in 'sklearn' package in Python. The classification model used is K- Nearest Neighbors where number of neighbors or 'n_neighbors' is 3.
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This model predicts the class of the flower from the input data of sepal length, sepal width, petal length and petal width. The data used for training this model is from the iris dataset present in 'sklearn' package in Python. The classification model used is K- Nearest Neighbors where number of neighbors or 'n_neighbors' is 3.
awiksshiith-narang/k_nearest_neighbors
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This model predicts the class of the flower from the input data of sepal length, sepal width, petal length and petal width. The data used for training this model is from the iris dataset present in 'sklearn' package in Python. The classification model used is K- Nearest Neighbors where number of neighbors or 'n_neighbors' is 3.
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