diff --git a/.idea/workspace.xml b/.idea/workspace.xml
index 299396f..fe9a205 100644
--- a/.idea/workspace.xml
+++ b/.idea/workspace.xml
@@ -4,6 +4,7 @@
+
@@ -48,7 +49,7 @@
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@@ -57,7 +58,7 @@
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@@ -67,8 +68,8 @@
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@@ -89,11 +90,11 @@
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@@ -131,11 +132,11 @@
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@@ -166,6 +167,7 @@
label_in_feature_columns
epoch
timeseries_to_supervised
+ batch_index
@@ -182,8 +184,8 @@
-
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@@ -226,7 +228,7 @@
-
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@@ -267,16 +269,15 @@
1588152877746
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@@ -365,16 +366,6 @@
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@@ -386,22 +377,32 @@
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diff --git a/train.py b/train.py
index 9bb8ca4..1ab36ce 100644
--- a/train.py
+++ b/train.py
@@ -90,8 +90,7 @@ def experiment(repeats, series, seed):
supervised = timeseries_to_supervised(diff_values, lag2)
supervised_values = supervised.values
# split data into train and test-sets
- test_data_num = 12
- train, test = supervised_values[0:-test_data_num], supervised_values[-test_data_num:]
+ train, test = supervised_values[0:-12], supervised_values[-12:]
# transform the scale of the data
print(test)
scaler, train_scaled, test_scaled = scale(train, test)
@@ -128,8 +127,8 @@ def experiment(repeats, series, seed):
# store forecast
predictions.append(yhat)
# report performance
- rmse = sqrt(mean_squared_error(raw_values[-test_data_num:], predictions))
- print(predictions, raw_values[-test_data_num:])
+ rmse = sqrt(mean_squared_error(raw_values[-12:], predictions))
+ print(predictions, raw_values[-12:])
print('%d) Test RMSE: %.3f' % (r + 1, rmse))
error_scores.append(rmse)
return error_scores