- 27 May, 2024 1 commit
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Nabiz authored
Normalized the time series with MinMaxScaler. For plotting of subplots it takes 50 Minutes, which is way too long, and have to run it on server. ARIMA gave 100% RMSE for non-scaled series. Now with scaling, but there is an issue with indexes for ARIMA....
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- 24 May, 2024 1 commit
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Nabiz authored
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- 23 May, 2024 1 commit
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Nabiz authored
The 7 variables are now loaded and split into train and test data sets. Subplot the time series with labels and units for a given location and level = 6. Have to run it on MN5
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- 22 May, 2024 1 commit
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Nabiz authored
Starting to apply multivariance time series analysis of the PISCES variables. First loading the XARRAYS....
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- 09 May, 2024 1 commit
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Nabiz authored
Now applying simple LSTM on PISCES INTDIAC data set. Next to use the Multivariate with Z, A, B, C, D, E, F PISCES variables from the excel table talked with Raffa
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- 08 May, 2024 4 commits
- 24 Apr, 2024 2 commits
- 19 Apr, 2024 1 commit
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Nabiz authored
By defining the autoregression of Z(t) = Y(t) as predictand and Z(t-1)=Y(t-1),A(t),B(t) as predictors to the synthetic data set to apply ARIMA and LSTM models. The RMSE is in the order of 5% ARIMA and 4% LSTM. With HYBRID model, simple averaging the statistical and NN ML models. Next will be uncertainty of forecast, XGBoost, PROPHET, ForrestClassifier Hybrid weighted average, majority voting model ensemble and runnig on MN5 with 9 Billion parameters
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- 18 Apr, 2024 2 commits
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Nabiz authored
By defining the autoregression of Z(t) = Z(t-1) + A(t) + B(t) to the synthetic data set to apply ARIMA and LSTM models. The RMSE is in the order of 8% with HYBRID model, simple mean of statistical and NN ML model, gives a better prediction 3%. Next will be uncertainty of forecast, XGBoost, weighted average, majority voting model ensemble. Hyperparameters and process it on MN5
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Nabiz authored
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- 10 Apr, 2024 1 commit
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Nabiz authored
Adding some noise to the determenistic series. Including the ARIMA search for RMSE min function to evaluate the best P D Q. Got the Integrated ARIMA(0,2,0) with RMSE of 6% which indicates an I(2) or Differentiation Function of order 2. Doing a manual MinMaxScaling to rescale the values of LTSM, since the RMSE of normalized values are higher in comparison to the original values, with RMSE of 9% for simple LSTM.
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- 03 Apr, 2024 2 commits
- 28 Mar, 2024 2 commits
- 27 Mar, 2024 2 commits
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Nabiz authored
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Nabiz authored
Testing multivariate LSTM and multivariate ARIMA on synthetic time series. The approach works. Next step would be with real PISCES data set. It is still unclear how to weights for linear lag correlation model should be applied. Using just multivariate ARIMA and LSTM or lagged multivariate, where the maximum cross correlation should be the constrain on time lagged external factors?
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- 07 Mar, 2024 3 commits
- 05 Mar, 2024 2 commits
- 01 Mar, 2024 2 commits
- 22 Feb, 2024 1 commit
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Nabiz authored
Adding prediction and plots for test data set. Playing with parameter settings putting them as constants.
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- 20 Feb, 2024 2 commits
- 13 Feb, 2024 5 commits