Thanks, If you will continue with this and can solve, please inform us what the solution was! ChatGPT proposes the next algorithms for this case Algorithm in MLTKWhen to UseStrengthsWeaknesses StateSpaceForecast(algo=StateSpaceForecast) Small seasonal datasets with trend Captures seasonality & trend Not designed for sparse series with many zeros ARIMA (algo=ARIMA) Strong seasonality, autocorrelation Handles short time series Needs continuous values (zeros can reduce model quality) LLP (Local Linear Projection) Simple, quick Light-weight Limited for complex patterns DenseNNRegressor / LSTM Complex, nonlinear series Can learn patterns over multiple users at once Requires MLTK deep learning toolkit, more tuning One-Class SVM / Isolation Forest (for anomaly detection instead of forecasting) Detecting abnormal future access Robust to sparse data Not a forecasting method per se Given your case — weekly time series, short history (26 points for training), seasonality (weekly), and sparsity — the StateSpaceForecast algorithm is usually the safest starting point in MLTK for this type of forecasting.
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