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")