from sklearn import tree from random import random from ImportCsv import importcsv import numpy as np # Load data rowData = importcsv("../spambase.data") data = [] for line in rowData: listLine = [] for value in line: listLine.append(float(value)) data.append(listLine) #print(data[0]) #print(len(data)) #### Specific fields#### usedData = [] usedValue = [] usedData1 = [] usedValue1 = [] for line in data: listLine = [] listLine1 = [] for k in range(len(line)): #if k in [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 23, 46, 51, 52, 53]: if k in [ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 23, 37, 46, 51, 52, 53
listNoPb = [] clsf1 = AdaBoostClassifier(n_estimators=200) #clsf2 = MLPClassifier() clsf2 = MLPClassifier(verbose=0, random_state=0, max_iter=max_iter, **param) clsf3 = KNeighborsClassifier(n_neighbors=nbNeighbors, weights=weightValue) clsf4 = tree.DecisionTreeClassifier() clsf5 = SVC(kernel="linear", C=0.2) tot = 0 totCancelled = 0 for tour in range(nbTurns): print(tour) # Load data rowData = importcsv(pathFile) data = [] for line in rowData: listLine = [] for value in line: listLine.append(float(value)) data.append(listLine) usedData = [] usedValue = [] for line in data: listLine = [] for k in range(len(line)): if k not in [27, 28, 31, 57, 3, 30, 32, 36, 39, 40, 46, 47]: listLine.append(line[k]) usedValue.append(line[-1])