Python sample_decision_tree_pruning 예제들

예제 #1

파일: dt_test_script.py 프로젝트: AnurimaPadwal/CSCI_567_Machine_Learning

def pruning_decision_tree_test():
    # load data
    X_train, y_train, X_test, y_test = data.sample_decision_tree_pruning()

    # build the tree
    dTree = decision_tree.DecisionTree()
    dTree.train(X_train, y_train)

    # print
    print('Your decision tree:')
    Utils.print_tree(dTree)
    print('My decision tree:')
    print(
        'branch 0{\n\tdeep: 0\n\tnum of samples for each class: 5 : 9 \n\tsplit by dim 0\n\tbranch 0->0{\n\t\tdeep: 1'
        '\n\t\tnum of samples for each class: 3 : 2 \n\t\tsplit by dim 1\n\t\tbranch 0->0->0{\n\t\t\tdeep: 2\n\t\t\t'
        'num of samples for each class: 3 \n\t\t\tclass:0\n\t\t}\n\t\tbranch 0->0->1{\n\t\t\tdeep: 2\n\t\t\tnum of '
        'samples for each class: 2 \n\t\t\tclass:1\n\t\t}\n\t}\n\tbranch 0->1{\n\t\tdeep: 1\n\t\tnum of samples for '
        'each class: 4 \n\t\tclass:1\n\t}\n\tbranch 0->2{\n\t\tdeep: 1\n\t\tnum of samples for each class: 2 : 3 '
        '\n\t\tsplit by dim 2\n\t\tbranch 0->2->0{\n\t\t\tdeep: 2\n\t\t\tnum of samples for each class: 3 \n\t\t\t'
        'class:1\n\t\t}\n\t\tbranch 0->2->1{\n\t\t\tdeep: 2\n\t\t\tnum of samples for each class: 2 \n\t\t\tclass:0'
        '\n\t\t}\n\t}\n}')

    Utils.reduced_error_prunning(dTree, X_test, y_test)

    print('Your decision tree after pruning:')
    Utils.print_tree(dTree)
    print('My decision tree after pruning:')
    print(
        'branch 0{\n\tdeep: 0\n\tnum of samples for each class: 5 : 9 \n\tsplit by dim 0\n\tbranch 0->0{\n\t\tdeep: '
        '1\n\t\tnum of samples for each class: 3 : 2 \n\t\tsplit by dim 1\n\t\tbranch 0->0->0{\n\t\t\tdeep: 2\n\t\t\t'
        'num of samples for each class: 3 \n\t\t\tclass:0\n\t\t}\n\t\tbranch 0->0->1{\n\t\t\tdeep: 2\n\t\t\tnum of '
        'samples for each class: 2 \n\t\t\tclass:1\n\t\t}\n\t}\n\tbranch 0->1{\n\t\tdeep: 1\n\t\tnum of samples for '
        'each class: 4 \n\t\tclass:1\n\t}\n\tbranch 0->2{\n\t\tdeep: 1\n\t\tnum of samples for each class: 2 : 3 '
        '\n\t\tclass:1\n\t}\n}')

예제 #2

def pruning_decision_tree_test():
    # load data
    X_train, y_train, X_test, y_test = data.sample_decision_tree_pruning()

    # build the tree
    dTree = decision_tree.ID3()
    dTree.train(X_train, y_train)

    # print
    print('Your decision tree:')
    Utils.printTree(dTree)

    Utils.reducedErrorPruning(dTree, X_test, y_test)
    print('Your decision tree after pruning:')
    Utils.printTree(dTree)