KFold Cross Validation: http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html ''' from __future__ import print_function import os import sys import tensorflow as tf import numpy as np from sklearn.metrics import f1_score, precision_score, recall_score, accuracy_score dir_path = os.path.dirname(os.path.realpath(__file__)) sys.path.insert(0, dir_path + '/../../utils') from config import DataDetails dd = DataDetails() def logistic_regression(dataset, labels, train_index, test_index, learning_rate, training_epochs, threshold, display_step=10): data_train, data_test = dataset[train_index], dataset[test_index] label_train, label_test = labels[train_index], labels[test_index] # Parameters
from config import DataDetails # import json from watson_developer_cloud import NaturalLanguageUnderstandingV1 from watson_developer_cloud.natural_language_understanding_v1 import Features, EntitiesOptions, SentimentOptions import nltk from nltk.tokenize import RegexpTokenizer sentence_tokenizer = RegexpTokenizer(r'\w+') foo = DataDetails() def get_from_wdc(sentence): ''' gets the sentiment score and entities in the sentence ''' API_KEY = foo.API_KEY natural_language_understanding = NaturalLanguageUnderstandingV1( version=API_KEY['version'], username=API_KEY['username'], password=API_KEY['password']) try: response = natural_language_understanding.analyze( text=sentence, features=Features(entities=EntitiesOptions(), sentiment=SentimentOptions())) # print(json.dumps(response, indent=2)) except: print("entered exception")