Decision Tree
Algorithms ID3 and C4.5 were implemented and the codes run with Python >= 2.7
Run
$ python Main.py [-id3|-c45|-c45p] [-t|-d|-i|-o FILE_PATH]
| Attribute | Description |
|---|---|
-id3 |
Execute the ID3 algorithm |
-c45 |
Execute the C45 algorithm |
-c45p |
Execute the C45 algorithm with pruning |
-t FILE |
Change the default file to train |
-d FILE |
Change the default file used on -c45p |
-i FILE |
File input with examples that you want test |
-o FILE |
File outut with results from examples tested by the algoritm |
Config
You always can change the configuration on the Configuration.py
| Attribute | Default value | Description |
|---|---|---|
| file_training_url | 'data/beach.csv' | File to train |
| file_depurated_url | 'data/beach_depurated.csv' | File with depurate rows to pruning |
| file_examples_url | 'data/examples.csv' | File with examples |
| file_output_url | 'data/output.csv' | File output |
| splitter | ',' | Split file when find this caracter |
| unknown_values | ['','-','?'] | values that describe a empty value |
| min_error | 1.0 | min erro to be use at pruning |
| print_tabs_num | 0 | used to format the print method tree |
| num_split_columns | 1 | number of columns removed (left side) of the file |
Notes
the attributes and values are not sensitive
pruning method only work on C45