""" Author: Federica Lionetto Date: November 6th, 2015 Description: Import modules used for training. How to run it: Include it in other python scripts. """ import ROOT as ROOT import os import time import sys sys.path.insert(0,'../CreateNtuples') from CreateNtuples_ToolsFile import * import subprocess import yaml import argparse import collections import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt from pylab import * import numpy as np import root_numpy as rnp import pandas as pd import root_pandas as rpd import pandas.core.common as com from pandas.core.index import Index from rep.utils import train_test_split from rep.utils import calc_feature_correlation_matrix from sklearn.metrics import roc_auc_score from sklearn.metrics import roc_curve from sklearn.metrics import auc from sklearn.metrics import zero_one_loss # from rep.data.storage import LabeledDataStorage # from rep.report import ClassificationReport from sklearn.tree import DecisionTreeClassifier from sklearn.grid_search import GridSearchCV from sklearn.cross_validation import train_test_split from sklearn.metrics import classification_report from rep.estimators import TMVAClassifier from rep.estimators import SklearnClassifier from rep.estimators.xgboost import XGBoostClassifier from rep.estimators.pybrain import PyBrainClassifier from rep.estimators.neurolab import NeurolabClassifier # from rep.estimators.theanets import TheanetsClassifier # Classifiers for uniformity from hep_ml.uboost import uBoostClassifier from hep_ml.gradientboosting import UGradientBoostingClassifier, KnnAdaLossFunction, KnnFlatnessLossFunction from sklearn.ensemble import GradientBoostingClassifier from sklearn.ensemble import ExtraTreesClassifier from hep_ml.commonutils import train_test_split from hep_ml import uboost, gradientboosting as ugb, losses from hep_ml.metrics import KnnBasedSDE, KnnBasedCvM from rep.report.metrics import RocAuc, LogLoss, OptimalMetric, ams from rep.metaml.gridsearch import RandomParameterOptimizer, AnnealingParameterOptimizer, SubgridParameterOptimizer, RegressionParameterOptimizer from rep.metaml import FoldingClassifier from rep.metaml import FoldingScorer from rep.metaml import GridOptimalSearchCV from rep.metaml import ClassifiersFactory from copy import deepcopy # Import modules for recursive feature elimination. from sklearn.svm import SVC from sklearn.cross_validation import StratifiedKFold from sklearn.cross_validation import LeaveOneOut from sklearn.feature_selection import RFECV from sklearn.feature_selection import RFE from sklearn.datasets import make_classification from sklearn.gaussian_process import GaussianProcess from sklearn.decomposition import PCA import itertools from itertools import combinations from itertools import chain import fnmatch from array import array import cPickle as pickle