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#Author: Marcel Pinheiro Caraciolo
#Confusion Matrix Generator
#Version: 0.1
#email: caraciol at gmail . com


from pprint import pprint as _pretty_print
import math

class ConfusionMatrix(object):

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class DecisionTree(object):
    """
    A decision tree object
    """        

    @staticmethod
    def count_results(data, item=True):
        """
        count the occurrences of each result in the data set
        """

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# Decision Tree Classifier
from sklearn import datasets
from sklearn import metrics
from sklearn.tree import DecisionTreeClassifier

# load the iris datasets
dataset = datasets.load_iris()
# fit a CART model to the data
model = DecisionTreeClassifier()
model.fit(dataset.data, dataset.target)

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#!/usr/bin/python
# -*- coding: utf-8 -*-

import subprocess


__all__ = ["transform"]
__version__ = '0.3'
__author__ = 'Christoph Burgmer <[email protected]>'
__url__ = 'http://github.com/cburgmer/upsidedown'

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# put timestamps in my bash history
export HISTTIMEFORMAT='%F %T '

# don't put duplicate commands into the history
export HISTCONTROL=ignoredups

# record only the most recent duplicated command (see above)
export HISTCONTROL=ignoreboth

# don't record these commands in the history; who cares about ls?

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# put timestamps in my bash history
export HISTTIMEFORMAT='%F %T '

# don't put duplicate commands into the history
export HISTCONTROL=ignoredups

# record only the most recent duplicated command (see above)
export HISTCONTROL=ignoreboth

# don't record these commands in the history; who cares about ls?