Brief tutorial Iris classification with GraphLab
| import graphlab as gl | |
| iris = gl.SFrame.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data', header=False) | |
| iris.rename({'X1': 'SepalLength', 'X2': 'SepalWidth', 'X3': 'PetalLength', 'X4': 'PetalWidth', 'X5': 'Species'}) | |
| train_data, test_data = iris.random_split(0.8) | |
| model = gl.classifier.create(train_data, target='Species', | |
| features = ['SepalLength', | |
| 'SepalWidth', | |
| 'PetalLength', | |
| 'PetalWidth']) | |
| predictions = model.classify(test_data) | |
| results = model.evaluate(test_data) |
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