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"Plot all predicitons in SlidingWindowValidation"
Maven
Dear All,
I wish to plot all my predictions made in my SlidingWindowValidation.
Currently I can only plot the predictions made in the FIRST iteration of the SlidingWindowValidation!
To plot the FIRST iteration I have to:
Set a breakpoint in RegressionPerformance.
Click on:
DataTable Tab.
PlotView
Plotter: Series
Index Dimension: Date
Plot series: [single_price, prediction(single_price)]
(A lot of work, would be nice if this could be automated)
Now how can I plot all predictions made in a sliding my SlidingWindowValidation.
I figured on each iteration I could write the datasets the comes out of ModelApplier to a new dataset.
The problem is CSVExampleSetWriter overwrites the old results.csv on each iteration!
Is there any way to make it append, instead of overwrite?
Regards,
Wessel
Example XML
Yes I know this is not the way to predict single_price.
But this should be the way to evaluate the performance of the prediction.
<operator name="Root" class="Process" expanded="yes">
<operator name="SalesExampleSetGenerator" class="SalesExampleSetGenerator">
<parameter key="number_examples" value="1500"/>
</operator>
<operator name="FeatureValueTypeFilter" class="FeatureValueTypeFilter">
</operator>
<operator name="ChangeAttributeRole" class="ChangeAttributeRole">
<parameter key="name" value="single_price"/>
<parameter key="target_role" value="label"/>
</operator>
<operator name="SlidingWindowValidation" class="SlidingWindowValidation" expanded="yes">
<parameter key="training_window_width" value="240"/>
<parameter key="test_window_width" value="24"/>
<parameter key="horizon" value="24"/>
<parameter key="average_performances_only" value="false"/>
<operator name="LinearRegression" class="LinearRegression">
</operator>
<operator name="OperatorChain" class="OperatorChain" expanded="yes">
<operator name="ModelApplier" class="ModelApplier">
<parameter key="keep_model" value="true"/>
<list key="application_parameters">
</list>
</operator>
<operator name="make transaction_id regular" class="ChangeAttributeRole">
<parameter key="name" value="transaction_id"/>
</operator>
<operator name="write to results" class="CSVExampleSetWriter">
<parameter key="csv_file" value="D:\wessel\Desktop\results.csv"/>
<parameter key="column_separator" value=","/>
</operator>
<operator name="RegressionPerformance" class="RegressionPerformance" breakpoints="after">
<parameter key="keep_example_set" value="true"/>
<parameter key="absolute_error" value="true"/>
<parameter key="correlation" value="true"/>
</operator>
</operator>
</operator>
</operator>
I wish to plot all my predictions made in my SlidingWindowValidation.
Currently I can only plot the predictions made in the FIRST iteration of the SlidingWindowValidation!
To plot the FIRST iteration I have to:
Set a breakpoint in RegressionPerformance.
Click on:
DataTable Tab.
PlotView
Plotter: Series
Index Dimension: Date
Plot series: [single_price, prediction(single_price)]
(A lot of work, would be nice if this could be automated)
Now how can I plot all predictions made in a sliding my SlidingWindowValidation.
I figured on each iteration I could write the datasets the comes out of ModelApplier to a new dataset.
The problem is CSVExampleSetWriter overwrites the old results.csv on each iteration!
Is there any way to make it append, instead of overwrite?
Regards,
Wessel
Example XML
Yes I know this is not the way to predict single_price.
But this should be the way to evaluate the performance of the prediction.
<operator name="Root" class="Process" expanded="yes">
<operator name="SalesExampleSetGenerator" class="SalesExampleSetGenerator">
<parameter key="number_examples" value="1500"/>
</operator>
<operator name="FeatureValueTypeFilter" class="FeatureValueTypeFilter">
</operator>
<operator name="ChangeAttributeRole" class="ChangeAttributeRole">
<parameter key="name" value="single_price"/>
<parameter key="target_role" value="label"/>
</operator>
<operator name="SlidingWindowValidation" class="SlidingWindowValidation" expanded="yes">
<parameter key="training_window_width" value="240"/>
<parameter key="test_window_width" value="24"/>
<parameter key="horizon" value="24"/>
<parameter key="average_performances_only" value="false"/>
<operator name="LinearRegression" class="LinearRegression">
</operator>
<operator name="OperatorChain" class="OperatorChain" expanded="yes">
<operator name="ModelApplier" class="ModelApplier">
<parameter key="keep_model" value="true"/>
<list key="application_parameters">
</list>
</operator>
<operator name="make transaction_id regular" class="ChangeAttributeRole">
<parameter key="name" value="transaction_id"/>
</operator>
<operator name="write to results" class="CSVExampleSetWriter">
<parameter key="csv_file" value="D:\wessel\Desktop\results.csv"/>
<parameter key="column_separator" value=","/>
</operator>
<operator name="RegressionPerformance" class="RegressionPerformance" breakpoints="after">
<parameter key="keep_example_set" value="true"/>
<parameter key="absolute_error" value="true"/>
<parameter key="correlation" value="true"/>
</operator>
</operator>
</operator>
</operator>
Tagged:
0
Answers
Use the much unloved process log and his chums, like this...
My version is now only logging the last example, of each iteration...
I think this is because your version only works with
<parameter key="test_window_width" value="1"/>
If I change it to 350, it only logs the first 1 in this window.
<operator name="Root" class="Process" expanded="yes">
<operator name="ExampleSetGenerator" class="ExampleSetGenerator">
<parameter key="target_function" value="random"/>
<parameter key="number_examples" value="1500"/>
<parameter key="number_of_attributes" value="1"/>
</operator>
<operator name="remove att1" class="FeatureNameFilter">
<parameter key="skip_features_with_name" value="att1"/>
</operator>
<operator name="IdTagging" class="IdTagging">
</operator>
<operator name="regular: id" class="ChangeAttributeRole">
<parameter key="name" value="id"/>
</operator>
<operator name="make sin(id/100)" class="AttributeConstruction">
<list key="function_descriptions">
<parameter key="sin(id/100)" value="sin(id/100)"/>
</list>
</operator>
<operator name="window size 100" class="MultivariateSeries2WindowExamples">
</operator>
<operator name="label: sin(id/100)-0" class="ChangeAttributeRole">
<parameter key="name" value="sin(id/100)-0"/>
<parameter key="target_role" value="label"/>
</operator>
<operator name="remove horizon attributes" class="FeatureNameFilter">
<parameter key="skip_features_with_name" value=".*-([0-9]|[1-4][0-9])"/>
<parameter key="except_features_with_name" value="id-0"/>
</operator>
<operator name="id-0 only" class="FeatureNameFilter">
<parameter key="skip_features_with_name" value="id-.*"/>
<parameter key="except_features_with_name" value="id-0"/>
</operator>
<operator name="1401 examples" class="SlidingWindowValidation" expanded="yes">
<parameter key="keep_example_set" value="true"/>
<parameter key="training_window_width" value="400"/>
<parameter key="test_window_width" value="350"/>
<parameter key="horizon" value="50"/>
<parameter key="average_performances_only" value="false"/>
<operator name="LinearRegression" class="LinearRegression">
</operator>
<operator name="OperatorChain" class="OperatorChain" expanded="yes">
<operator name="ModelApplier" class="ModelApplier">
<parameter key="keep_model" value="true"/>
<list key="application_parameters">
</list>
</operator>
<operator name="RegressionPerformance" class="RegressionPerformance">
<parameter key="keep_example_set" value="true"/>
<parameter key="absolute_error" value="true"/>
<parameter key="correlation" value="true"/>
</operator>
<operator name="id-0" class="Data2Log">
<parameter key="attribute_name" value="id-0"/>
<parameter key="example_index" value="-1"/>
</operator>
<operator name="sin(id/100)-0" class="Data2Log">
<parameter key="attribute_name" value="sin(id/100)-0"/>
<parameter key="example_index" value="-1"/>
</operator>
<operator name="prediction(sin(id/100)-0)" class="Data2Log">
<parameter key="attribute_name" value="prediction(sin(id/100)-0)"/>
<parameter key="example_index" value="-1"/>
</operator>
<operator name="ProcessLog" class="ProcessLog">
<list key="log">
<parameter key="id-0" value="operator.id-0.value.data_value"/>
<parameter key="sin(id/100)-0" value="operator.sin(id/100)-0.value.data_value"/>
<parameter key="prediction(sin(id/100)-0)" value="operator.prediction(sin(id/100)-0).value.data_value"/>
</list>
</operator>
</operator>
</operator>
</operator>
just an idea, but if you want to merge all results, the following process variation could give you an impression of another way: I did not really test the process, so the setup might fail. But the way should be clear...
Greetings,
Sebastian
Although I don't understand why the 2 RegressionPerformance don't give the same results.
21 vs 22...
Regards,
Wessel
<operator name="Root" class="Process" expanded="yes">
<operator name="SalesExampleSetGenerator" class="SalesExampleSetGenerator">
<parameter key="number_examples" value="1500"/>
</operator>
<operator name="FeatureValueTypeFilter" class="FeatureValueTypeFilter">
</operator>
<operator name="ChangeAttributeRole" class="ChangeAttributeRole">
<parameter key="name" value="single_price"/>
<parameter key="target_role" value="label"/>
</operator>
<operator name="SlidingWindowValidation" class="SlidingWindowValidation" expanded="yes">
<parameter key="training_window_width" value="240"/>
<parameter key="test_window_width" value="24"/>
<parameter key="horizon" value="24"/>
<parameter key="average_performances_only" value="false"/>
<operator name="LinearRegression" class="LinearRegression">
</operator>
<operator name="OperatorChain" class="OperatorChain" expanded="yes">
<operator name="ModelApplier" class="ModelApplier">
<parameter key="keep_model" value="true"/>
<list key="application_parameters">
</list>
</operator>
<operator name="make transaction_id regular" class="ChangeAttributeRole">
<parameter key="name" value="transaction_id"/>
</operator>
<operator name="MergeAndStoreResults" class="OperatorChain" expanded="yes">
<operator name="IOMultiplier" class="IOMultiplier">
<parameter key="io_object" value="ExampleSet"/>
</operator>
<operator name="ExceptionHandling" class="ExceptionHandling" expanded="yes">
<operator name="IORetriever (3)" class="IORetriever">
<parameter key="name" value="ExampleSetStore"/>
<parameter key="io_object" value="ExampleSet"/>
<parameter key="remove_from_store" value="false"/>
</operator>
</operator>
<operator name="ExampleSetMerge" class="ExampleSetMerge">
<parameter key="merge_type" value="first_two"/>
</operator>
<operator name="IOStorer" class="IOStorer">
<parameter key="name" value="ExampleSetStore"/>
<parameter key="io_object" value="ExampleSet"/>
</operator>
</operator>
<operator name="IORetriever (2)" class="IORetriever">
<parameter key="name" value="ExampleSetStore"/>
<parameter key="io_object" value="ExampleSet"/>
<parameter key="remove_from_store" value="false"/>
</operator>
<operator name="RegressionPerformance" class="RegressionPerformance">
<parameter key="keep_example_set" value="true"/>
<parameter key="absolute_error" value="true"/>
<parameter key="correlation" value="true"/>
</operator>
<operator name="IOMultiplier (2)" class="IOMultiplier" activated="no">
<parameter key="io_object" value="PerformanceVector"/>
</operator>
</operator>
</operator>
<operator name="IORetriever" class="IORetriever">
<parameter key="name" value="ExampleSetStore"/>
<parameter key="io_object" value="ExampleSet"/>
<parameter key="remove_from_store" value="false"/>
</operator>
<operator name="RegressionPerformance (2)" class="RegressionPerformance">
<parameter key="keep_example_set" value="true"/>
<parameter key="absolute_error" value="true"/>
<parameter key="correlation" value="true"/>
</operator>
</operator>