No longer maintained. Moved to machine-learning-classifier-iris
.
A machine learning classifier for identifying/predicting the type of iris (ie. setosa, versicolor, or virginica) based on its (petal, sepal) features.
Data is:
- loaded
- described
- visualized (somewhat)
- split into 'train' and 'test' sets
Then:
- (2) machine learning models (ie. classifiers; supervised learning algorithms) are created;
- the models are 'fit' to the training data;
- (class) predictions are made for new/out-of-sample/test data;
- the accuracy of the algorithms is evaluated and compared.
- Python v3.7.0
- Jupyter Notebook server v5.6.0
- IPython v6.5.0
- Iris flowers dataset (included with scikit-learn)
(All copyrights for the above remain with their respective owners.)
Copyright (c) 2018 Heini Fagerlund. Licensed under the MIT License.