from SentimentAnalysis import SentimentAnalyzer from Evaluation import Evaluator api_key = 's6J10zzMfa9Vm5q1AufUu4gTovcVJEmo' ''' # perform Sentiment Analysis sa = SentimentAnalyzer(api_key) target_file = sa.perform_analysis('dow jones', 1980, 11, "../data/indices/DJI.csv", "../data/indices/DJI_sentiments.csv") ''' # model evaluation ev = Evaluator( model_path='../models/normalized_sentiments.h5', eval_data_path='../data/dow_jones_stocks/sentiments/dataset_3/NKE.csv', scaler_path='../models/normalized_sentiments_scaler.save') ev.create_prediction_data(normalize=True) print("Market Return: {}\nModel Return: {}".format( ev.market_return(), ev.model_return(kapital=100))) ev.plot_predictions()