项目作者： danglingP0inter

项目描述：

  Implementing k – Nearest Neighbor classifier from scratch to classify data from the famous IRIS dataset of scikit-learn.

高级语言： Python

项目主页：

项目地址: git://github.com/danglingP0inter/Iris-flower-classification-using-ML-classifiers.git

创建时间： 2019-01-20T19:07:33Z
项目社区：https://github.com/danglingP0inter/Iris-flower-classification-using-ML-classifiers
开源协议：
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Iris-flower-classification-using-ML-classifiers

Implementation of k – Nearest Neighbor classifier from scratch to classify data from the famous IRIS dataset of scikit-learn.

Some lines of the code have been commented deliberately. You can uncomment them to compare the accuracy of the model with default kNN implementation provided by scikit-learn.

Among all well-known ML classifiers, kNN is found to be performing best on this perticular dataset.

For 80:20 train-test split, kNN model has accuracy of 93.3%.