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KaleabTessera/prediction.py

Created December 11, 2018 18:48
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prediction.py
# Load model with best rMse and make prediction
fileName = "results/" + "bestRegressionModel_" + str(LineaReggressionMetrics.ROOT_MEAN_SQUARED_ERROR.name) + ".sav"
bestRegression = joblib.load(fileName)
#Example ICO
#Format - price_usd,price_btc,total_supply,market_cap_usd,available_supply,usd_raised,eth_price_launch,btc_price_launch,ico_duration,month,day,country
example_x = np.array([1.71456,0.00019931,1000000000,905793616,528295082,24000000,297.63,3420.4,7,8,9,182])
y_pred = makePrediction(bestRegression,example_x)
print("Predicted value of example ICO after six months: ",y_pred )
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