GaelVaroquaux

'''
Non-parametric computation of entropy and mutual-information

Adapted by G Varoquaux for code created by R Brette, itself
from several papers (see in the code).

This code is maintained at https://github.com/mutualinfo/mutual_info 
Please download the latest code there, to have improvements and 
bug fixes.

boates

def splitData(df, trainPerc=0.6, cvPerc=0.2, testPerc=0.2):
    """
    return: training, cv, test
            (as pandas dataframes)
    params:
              df: pandas dataframe
       trainPerc: float | percentage of data for trainin set (default=0.6
          cvPerc: float | percentage of data for cross validation set (default=0.2)
        testPerc: float | percentage of data for test set (default=0.2)
                  (trainPerc + cvPerc + testPerc must equal 1.0)

upsuper

一行 Python 实现树

使用 Python 内置的 defaultdict，我们可以很容易的定义一个树形数据结构：

def tree(): return defaultdict(tree)

就是这样！