iprocheta

import pandas as pd
from sklearn.ensemble import RandomForestClassifier
#from sklearn.tree import DecisionTreeClassifier
import numpy as np
import sklearn.metrics as sk
from sklearn.metrics import classification_report
import itertools
import matplotlib.pyplot as plt
from sklearn.metrics import confusion_matrix
Ami_data = pd.read_csv("E:\\data\\v2\\dataset.csv",delimiter=',', encoding="utf-8-sig")

iprocheta

iprocheta

iprocheta

import numpy as np
import pandas as pd
from sklearn.cross_validation import train_test_split
from sklearn.tree import DecisionTreeClassifier
from sklearn.metrics import accuracy_score
from sklearn.metrics import precision_score
from sklearn.metrics import recall_score
from sklearn.metrics import confusion_matrix
from sklearn.metrics import precision_recall_curve
from sklearn.metrics import auc

iprocheta

with open(r"E:\clf_entropy.txt", "w") as f:
    f = tree.export_graphviz(clf_entropy, out_file=f)
        print(clf_entropy.get_params(deep=True))