Python create_dataset Examples

Example #1

File: trees_test.py Project: Shitaibin/machine-learning-in-action-refactoring

    def test_create_tree(self):
        """Unittest for create tree.

        :return:
        """
        data, feat_names = trees.create_dataset()
        decision_tree = {
            'no surfacing': {
                0: 'no',
                1: {
                    'flippers': {
                        0: 'no',
                        1: 'yes'
                    }
                }
            }
        }
        self.assertEqual(decision_tree, trees.create_tree(data, feat_names))

        data = [[1, 2, 'yes'], [1, 3, 'yes'], [2, 3, 'no']]
        feat_names = ['no surfacing', 'flippers']
        decision_tree = {'no surfacing': {1: 'yes', 2: 'no'}}
        self.assertEqual(decision_tree, trees.create_tree(data, feat_names))

Example #2

import trees
import tree_plotter

my_data, _ = trees.create_dataset()
print(trees.cal_shannon_ent(my_data))

my_data[0][-1] = 'maybe'
print(trees.cal_shannon_ent(my_data))

my_data, _ = trees.create_dataset()
trees.split_dataset(my_data, 0, 1)
trees.split_dataset(my_data, 0, 0)

trees.choose_best_feature_to_split(my_data)

my_data, labels = trees.create_dataset()
trees.create_tree(my_data, labels)

tree_plotter.create_plot()

Example #3

File: trees_test.py Project: Shitaibin/machine-learning-in-action-refactoring

 def test_calc_entropy(self):
     data, feat_names = trees.create_dataset()
     entropy = -(0.4 * log(0.4, 2) + 0.6 * log(0.6, 2))
     self.assertEqual(entropy, trees.calc_entropy(data))

Example #4

import trees

dataset, labels = trees.create_dataset()
print(dataset)
entropy = trees.entropy(dataset)
print(entropy)