在服务器上修改bug，测试完成。

l00c00l · Jan 22, 2020 · 4f98a60 · 4f98a60
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commit 4f98a60
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Showing 37 changed files with 4 additions and 4 deletions.
diff --git a/11/AR.png b/11/AR.png
diff --git a/11/AR_predict.png b/11/AR_predict.png
diff --git a/11/AbsoluteChange.png b/11/AbsoluteChange.png
diff --git a/11/Arima_predict.png b/11/Arima_predict.png
diff --git a/11/Compare.png b/11/Compare.png
diff --git a/11/DynamicFactor.png b/11/DynamicFactor.png
diff --git a/11/ExpandingMicrosoft.png b/11/ExpandingMicrosoft.png
diff --git a/11/Kansas_humidity.png b/11/Kansas_humidity.png
diff --git a/11/NormalizedCompare.png b/11/NormalizedCompare.png
diff --git a/11/Return1.png b/11/Return1.png
diff --git a/11/Return2.png b/11/Return2.png
diff --git a/11/RollongGoogle.png b/11/RollongGoogle.png
diff --git a/11/Var_predict.png b/11/Var_predict.png
diff --git a/11/acf.png b/11/acf.png
diff --git a/11/arma_forcast.png b/11/arma_forcast.png
diff --git a/11/decomposed.png b/11/decomposed.png
diff --git a/11/google.png b/11/google.png
diff --git a/11/google_arma.png b/11/google_arma.png
diff --git a/11/google_trend.png b/11/google_trend.png
diff --git a/11/humid_arma.png b/11/humid_arma.png
diff --git a/11/ma1.png b/11/ma1.png
diff --git a/11/ma_forcast.png b/11/ma_forcast.png
diff --git a/11/ms_pacf.png b/11/ms_pacf.png
diff --git a/11/nonstationary.png b/11/nonstationary.png
diff --git a/11/pacf.png b/11/pacf.png
diff --git a/11/percent.png b/11/percent.png
diff --git a/11/random_hist.png b/11/random_hist.png
diff --git a/11/random_walk.png b/11/random_walk.png
diff --git a/11/sarimax.png b/11/sarimax.png
diff --git a/11/sarimax_test.png b/11/sarimax_test.png
diff --git a/11/shifted.png b/11/shifted.png
diff --git a/11/stationary.png b/11/stationary.png
diff --git a/11/timeseries.py b/11/timeseries.py
@@ -11,7 +11,7 @@
 # 上面设matplotlib的模板，对可视化时间序列数据很有用。
 from pylab import rcParams
 #from plotly import tools
-import chart_studio.plotly as py
+#import chart_studio.plotly as py
 #from plotly.offline import init_notebook_mode, iplot
 # init_notebook_mode(connected = True)
 #import plotly.graph_objs as go
@@ -26,7 +26,7 @@
 from statsmodels.tsa.arima_model import ARIMA
 import math
 # import mpl_finance as mpf
-# from sklearn.metrics import mean_squared_error
+from sklearn.metrics import mean_squared_error
 
 
 if __name__ == "__main__":
@@ -445,6 +445,6 @@
 	fig = result.plot_diagnostics()
 	fig.savefig("DynamicFactor.png")
 	# 计算误差
-	rmse = math.sqrt(mean_squared_error(train_sample[1:502], predicted_result))
+	rmse = math.sqrt(mean_squared_error(train_sample[1:1002], predicted_result))
 	print("The root mean squared error is {}.".format(rmse))
-
+
diff --git a/11/unobserve.png b/11/unobserve.png
diff --git a/11/unobserve_test.png b/11/unobserve_test.png
diff --git a/11/whitenoise.png b/11/whitenoise.png
diff --git a/11/wn_acf.png b/11/wn_acf.png