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License: MIT License
Implementation of C4.5 algorithm in python.
License: MIT License
This is an implementation of C4.5 algorithm (http://en.wikipedia.org/wiki/C4.5_algorithm). Data table has folowing format: { "<column name>': [<column values>], "<column name>': [<column values>], ... } The main functions are located in file mine.py: - "mine_c45" is an implementation of the C4.5 algorithm. To run the algorithm you need to pass a table in the format described above; - "tree_to_rules" is a function for generate rules from desicion tree.
Hi! Thank you for sharing your implementation of C4.5 (over 10 years ago!!)
I just wanted to point out a simple fix that can improve by order of magnitudes the runtime of the algorithm, in some datasets. I hope this will be useful for people like me that will find this repo in the future.
return {k: [v[i] for i in range(len(v)) if i in ind] for k, v in t.items()}
Here, it is useless to cycle over range and ind. You can simplify as follows:
return {k: [v[i] for i in ind] for k, v in t.items()}
On my machine, running the updated version on the mushroom UCI dataset takes <1s, while before it took about 50 seconds.
I plan to release a repository that will include your updated code. (hoping that's ok!)
Thanks!
sklearn has no decent tree implementation.
Traceback (most recent call last):
File "c45test.py", line 2, in
from c45 import *
File "/home/s1617346/Desktop/C45algorithm-master/c45.py", line 2, in
import utils
File "/home/s1617346/Desktop/C45algorithm-master/utils.py", line 42
return {k: [v[i] for i in range(len(v)) if i in ind] for k, v in t.items()}
^
SyntaxError: invalid syntax
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