========================================================================
WiSARD / WNN BACKTEST REPORT
Rows: 277
========================================================================

--- BASELINE: Pure Linear Extrapolation (P1) ---

Power        MAE    RMSE   Median      Max    %<5u
----------------------------------------------------
p0.10       8.10   11.93     5.00    61.09   49.8%
p0.42       8.68   12.70     5.33    64.35   49.1%
p0.74       9.37   13.59     5.75    67.94   46.6%
p1.07      10.18   14.62     6.24    72.04   40.1%
p1.39      11.03   15.72     7.26    76.48   38.6%
p1.71      11.97   16.96     8.38    81.92   35.7%
p2.03      13.22   18.49     9.62    87.57   32.5%
p2.36      14.64   20.24    11.00    94.46   29.2%
p2.68      16.46   22.43    12.77   102.17   26.4%
p3.00      18.70   25.16    14.00   111.15   23.5%

--- WiSARD: K=8,  276 bits (no XOR) | 35 nodes ---

Power        MAE    RMSE   Median      Max    %<5u    vs P1
--------------------------------------------------------------
p0.10       6.07    9.22     4.07    42.89   56.7%    -2.03
p0.42       6.61    9.87     4.25    46.12   53.8%    -2.07
p0.74       7.27   10.67     5.06    49.69   49.8%    -2.10
p1.07       8.04   11.62     5.90    53.78   46.2%    -2.14
p1.39       8.88   12.65     6.48    58.22   43.0%    -2.15
p1.71       9.88   13.87     7.60    63.58   39.4%    -2.09
p2.03      11.13   15.40     8.65    69.24   33.6%    -2.10
p2.36      12.57   17.15     9.82    76.11   30.0%    -2.07
p2.68      14.45   19.39    11.21    83.82   27.4%    -2.01
p3.00      16.75   22.20    13.13    92.80   23.5%    -1.95

  Learning curve (p1.07): first-50 MAE=14.99  last-50 MAE=5.55
  LUT fill: 1405 / 8960 entries (15.681%)

--- WiSARD: K=8,  345 bits (with XOR) | 44 nodes ---

Power        MAE    RMSE   Median      Max    %<5u    vs P1
--------------------------------------------------------------
p0.10       6.19    9.17     4.11    41.57   59.2%    -1.92
p0.42       6.73    9.84     4.71    44.80   52.3%    -1.95
p0.74       7.39   10.65     5.04    48.37   49.8%    -1.98
p1.07       8.17   11.63     5.80    52.45   45.8%    -2.01
p1.39       9.00   12.67     6.60    56.89   42.6%    -2.02
p1.71       9.98   13.89     7.52    62.26   37.9%    -2.00
p2.03      11.21   15.42     8.68    67.92   32.9%    -2.01
p2.36      12.65   17.18     9.73    74.80   28.9%    -1.99
p2.68      14.51   19.41    11.26    82.50   26.4%    -1.95
p3.00      16.79   22.22    13.07    91.48   23.8%    -1.90

  Learning curve (p1.07): first-50 MAE=15.17  last-50 MAE=5.78
  LUT fill: 1520 / 11264 entries (13.494%)

--- WiSARD: K=12, 276 bits (no XOR) | 23 nodes ---

Power        MAE    RMSE   Median      Max    %<5u    vs P1
--------------------------------------------------------------
p0.10       5.85    9.07     3.70    42.14   57.8%    -2.26
p0.42       6.38    9.69     4.28    45.36   54.2%    -2.30
p0.74       7.02   10.44     5.17    48.93   49.5%    -2.35
p1.07       7.81   11.37     5.91    53.02   44.4%    -2.37
p1.39       8.63   12.37     6.43    57.45   43.0%    -2.40
p1.71       9.63   13.57     7.38    62.81   39.0%    -2.34
p2.03      10.86   15.09     8.20    68.47   33.2%    -2.36
p2.36      12.32   16.84     9.55    75.34   30.0%    -2.31
p2.68      14.23   19.08    10.76    83.05   24.9%    -2.23
p3.00      16.54   21.90    12.54    92.03   23.8%    -2.16

  Learning curve (p1.07): first-50 MAE=14.43  last-50 MAE=5.13
  LUT fill: 1969 / 94208 entries (2.090%)

--- WiSARD: K=12, 345 bits (with XOR) | 29 nodes ---

Power        MAE    RMSE   Median      Max    %<5u    vs P1
--------------------------------------------------------------
p0.10       5.96    9.15     3.89    43.90   58.5%    -2.15
p0.42       6.49    9.78     4.45    47.12   55.2%    -2.19
p0.74       7.14   10.55     4.88    50.69   50.9%    -2.23
p1.07       7.92   11.50     5.75    54.77   46.9%    -2.26
p1.39       8.77   12.52     6.21    59.21   41.2%    -2.25
p1.71       9.74   13.73     7.09    64.56   38.3%    -2.23
p2.03      11.02   15.26     8.29    70.22   32.5%    -2.21
p2.36      12.48   17.02     9.51    77.09   28.9%    -2.16
p2.68      14.34   19.26    10.74    84.80   24.9%    -2.11
p3.00      16.64   22.08    12.52    93.78   22.4%    -2.06

  Learning curve (p1.07): first-50 MAE=14.85  last-50 MAE=5.27
  LUT fill: 2167 / 118784 entries (1.824%)


========================================================================
SUMMARY — Average MAE across all power levels
========================================================================

Config                             Avg MAE    vs P1
----------------------------------------------------
P1 (linear baseline)                12.235
K=8,  276 bits (no XOR)             10.165   -2.071
K=8,  345 bits (with XOR)           10.263   -1.973
K=12, 276 bits (no XOR)              9.927   -2.308
K=12, 345 bits (with XOR)           10.051   -2.184


Note: negative 'vs P1' = improvement; positive = worse than linear baseline.
Learning is online: each row trains BEFORE the next prediction.
WiSARD learns the residual correction on top of linear extrapolation.
