InferenceShifter is used to align predictions with actual values for comparison, hence its usage inside the if plot: block. It's especially useful for multistep prediction models where there might be, for example, predictions for 1, 5, and 10 steps ahead.
On Wed, Sep 2, 2015 at 7:15 AM, 曾惟如 <[email protected]> wrote: > hello nupic: > > recently, I am learning the source code of the program hotgym prodiction. > and there are something I can't understand. > > In the document of Online Prediction Framework( > https://github.com/numenta/nupic/wiki/Online-Prediction-Framework), there > a introduction(Shifting Inferences) which is about the shift, but i can't > get what dose that mean. So I want to ask some question. > > 1: what dose shifter do?. What dose the code "result - > shifter.shift(result)" do?. You can see some codes below. > > 2: Why some program do not use the class InferenceShifter? I have read > some other source code like One Hot Gym Anomaly and CPU Usage. in that > code, there no the step "shifter = InferenceShifter()", it dosen't use the > class InferenceShifter. So i want to konw what is situation of use the > class InferenceShifter. > > "field=kw_energy_consumption"]) > > if plot: > result = shifter.shift(result) > > prediction = result.inferences["multiStepBestPredictions"][1] > output.write([timestamp], [consumption], [prediction]) > > (the code is in the line 124 of the hotgym_prediction's run.py) > > Please bear the bad English, andthanks in advance!! >
