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Random Forest for multiclass problems in python

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RandomForestPython

Requirements

python Download

How to run

decision-tree.py accepts parameters passed via the command line. The possible paramters are:

  • Filename for training (Required, must be the first argument after 'python decision_tree_multiclass.py')

  • Datatype flag (-d) followed by datatype filename (Optional, defaults to 'datatypes.csv')

  • Print flag (-s) (Optional, causes the dataset)

  • Validate flag (-v) followed by validate filename (Optional, specifies file to use for validation)

  • Test flag (-t) followed by test filename (Optional, specifies file to use for testing)

Examples

#####Example 1

python decision_tree_multiclass.py data/iris_training.arff -t data/iris_test.arff

This command runs decision_tree.py with iris_training.csv as the training set and iris_test.csv as the test set. The classifier is not specified so it defaults to the last column in the training set. Printing is not enabled. #####Example 2

python decision_tree_multiclass.py data/iris_training.arff -t data/iris_test.arff -s

This command runs decision_tree.py with iris_training.csv as the training set and iris_test.csv as the test set. The classifier is not specified so it defaults to the last column in the training set. Printing is enabled.

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