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Update functions.py
Browse files- functions.py +27 -3
functions.py
CHANGED
@@ -339,7 +339,9 @@ class Models(object):
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predictions = scaler.inverse_transform(predictions)
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#rmse = np.sqrt(np.mean(((predictions - y_test) ** 2)))
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global r_squared_score
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r_squared_score = round(r2_score(y_test, predictions),2)
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#print('Rmse Score: ', round(rmse),2)
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print('R2 Score: ', r_squared_score)
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@@ -439,20 +441,42 @@ class Models(object):
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mode = 'lines',
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name = '7-day Prediction',
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line=dict(width=1,color="#EE3B3B"))
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layout = go.Layout(
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title = 'Next 7 days stock price prediction of ' + str(ticker),
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xaxis = {'title' : "Date"},
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yaxis = {'title' : "Price ($)"}
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)
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fig = go.Figure(data=[plot_1, plot_2], layout=layout)
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fig.update_layout(template='plotly_dark',autosize=True)
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fig.update_layout(legend=dict(
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orientation="h",
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yanchor="bottom",
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y=1.02,
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xanchor="right",
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x=1
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return fig
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predictions = scaler.inverse_transform(predictions)
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#rmse = np.sqrt(np.mean(((predictions - y_test) ** 2)))
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global r_squared_score
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global rmse
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r_squared_score = round(r2_score(y_test, predictions),2)
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rmse = np.sqrt(np.mean(((predictions - y_test) ** 2)))
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#print('Rmse Score: ', round(rmse),2)
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print('R2 Score: ', r_squared_score)
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mode = 'lines',
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name = '7-day Prediction',
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line=dict(width=1,color="#EE3B3B"))
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plot_3 = go.Scatter(
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x = finaldfPredictions['Date'][:1],
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y = finaldfPredictions['Adj Close'][:1],
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mode = 'markers',
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name = 'Latest Actual Closing Price',
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line=dict(width=1))
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layout = go.Layout(
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title = 'Next 7 days stock price prediction of ' + str(ticker),
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xaxis = {'title' : "Date"},
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yaxis = {'title' : "Price ($)"}
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)
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fig = go.Figure(data=[plot_1, plot_2,plot_3], layout=layout)
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fig.update_layout(template='plotly_dark',autosize=True)
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fig.update_layout(legend=dict(
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orientation="h",
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yanchor="bottom",
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y=1.02,
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xanchor="right",
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x=1),
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annotations = [dict(x=0.5,
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y=0,
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xref='paper',
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yref='paper',
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text="Current In Sample R- Squared : " + str(r_squared_score*100) + " % \n",
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showarrow = False)],
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xaxis=dict(showgrid=False),
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yaxis=dict(showgrid=False)
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)
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fig.add_annotation(x=0.5,
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y=0.05,
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xref='paper',
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yref='paper',
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text="Current In Sample Root Mean Square Error : " + str(round(rmse,2)) + " % ",
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showarrow=False)
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return fig
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