25 lines
649 B
Python
25 lines
649 B
Python
import tensorflow as tf
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import pywatts.db
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from pywatts.routines import *
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PREDICT_QUERY = "query-sample_1hour.json"
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PREDICT_RESULT = PREDICT_QUERY.replace("query", "result")
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QUERY_ID = 0
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pred_query = input_query("../sample_data/" + PREDICT_QUERY, QUERY_ID)
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pred_result = input_result("../sample_data/" + PREDICT_RESULT, QUERY_ID)
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# Define feature columns and initialize Regressor
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feature_col = [tf.feature_column.numeric_column(str(idx)) for idx in range(336)]
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n = pywatts.neural.Net(feature_cols=feature_col)
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prediction = predict(n, pred_query)
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print(prediction)
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print(pred_result)
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pywatts.routines.eval_prediction(prediction, pred_result)
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