[DOC] Bakeoff error note and dataset resample indices update (#219)

* bakeoff note

* correction

* italics

tsml_eval/experiments/experiments.py

@@ -48,7 +48,7 @@
 )
 from tsml_eval.utils.memory_recorder import record_max_memory
 
-if os.getenv("MEMRECORD_INTERVAL") is not None:
+if os.getenv("MEMRECORD_INTERVAL") is not None:  # pragma: no cover
     TEMP = os.getenv("MEMRECORD_INTERVAL")
     MEMRECORD_INTERVAL = float(TEMP) if isinstance(TEMP, str) else 5.0
 else:

tsml_eval/publications/y2023/tsc_bakeoff/results/table_c4.csv

@@ -0,0 +1,31 @@
+Estimators:,,MR-H,HC2,RDST,QUANT,FP,H-IT,W 2.0,PF
+AconityMINIPrinterLarge_eq,,0.957010135,0.954560811,0.958164414,0.943890766,0.946143018,0.964893018,0.953378378,0.91044482
+AconityMINIPrinterSmall_eq,,0.977511416,0.978538813,0.975570776,0.975799087,0.971917808,0.97739726,0.976255708,0.964041096
+AllGestureWiimoteX_eq,,0.765285714,0.737904762,0.710333333,0.676333333,0.688238095,0.814428571,0.700761905,0.766761905
+AllGestureWiimoteY_eq,,0.806285714,0.776047619,0.732809524,0.705142857,0.714285714,0.838333333,0.731571429,0.753380952
+AllGestureWiimoteZ_eq,,0.730714286,0.728904762,0.677619048,0.661809524,0.674904762,0.782428571,0.691666667,0.741904762
+AsphaltObstaclesUni_eq,,0.88516624,0.889002558,0.879965899,0.842796249,0.857203751,0.911935209,0.883716965,0.888746803
+AsphaltPavementTypeUni_eq,,0.917550505,0.890814394,0.892392677,0.935921717,0.929324495,0.938383838,0.799558081,0.892645202
+AsphaltRegularityUni_eq,,0.986861962,0.958055925,0.976919663,0.988726143,0.98659565,0.985619174,0.93271194,0.983044829
+Colposcopy,,0.375907591,0.397359736,0.396039604,0.424092409,0.411881188,0.361056106,0.382838284,0.329042904
+Covid3Month_disc,,0.608743169,0.655191257,0.653005464,0.614754098,0.619125683,0.469398907,0.609836066,0.603278689
+DodgerLoopDay_nmv,,0.548051948,0.607792208,0.610822511,0.611688312,0.574458874,0.526406926,0.603896104,0.588311688
+DodgerLoopGame_nmv,,0.865354331,0.84488189,0.80839895,0.833070866,0.848818898,0.782414698,0.842519685,0.880577428
+DodgerLoopWeekend_nmv,,0.980952381,0.983597884,0.983597884,0.984920635,0.978835979,0.97010582,0.979365079,0.984656085
+ElectricDeviceDetection,,0.901769285,0.891525124,0.9002477,0.902043524,0.896779901,0.751380042,0.893108634,0.889915074
+FloodModeling1_disc,,0.935313531,0.872277228,0.869471947,0.944884488,0.94950495,0.920627063,0.799174917,0.933168317
+FloodModeling2_disc,,0.976451078,0.934162521,0.932338308,0.978109453,0.971973466,0.965008292,0.931674959,0.965671642
+FloodModeling3_disc,,0.90942029,0.800181159,0.820833333,0.926992754,0.941847826,0.885144928,0.717210145,0.905978261
+GestureMidAirD1_eq,,0.773589744,0.78025641,0.742564103,0.710769231,0.706666667,0.753589744,0.733333333,0.644615385
+GestureMidAirD2_eq,,0.636666667,0.648205128,0.622051282,0.617692308,0.613589744,0.599487179,0.633333333,0.539487179
+GestureMidAirD3_eq,,0.484615385,0.531794872,0.519230769,0.47025641,0.474615385,0.396153846,0.447179487,0.345384615
+GesturePebbleZ1_eq,,0.957170543,0.959496124,0.971317829,0.945155039,0.943992248,0.970930233,0.961046512,0.899612403
+GesturePebbleZ2_eq,,0.967932489,0.967510549,0.974894515,0.94978903,0.944092827,0.961181435,0.969198312,0.907805907
+KeplerLightCurves,,0.924561404,0.966583124,0.928404344,0.947953216,0.96566416,0.750710109,0.923893066,0.895238095
+MelbournePedestrian_nmv,,0.963145034,0.947462987,0.959465287,0.970590772,0.964424321,0.967773466,0.920885439,0.952838867
+PLAID_eq,,0.939168218,0.893482309,0.917752948,0.916076971,0.888702669,0.47591558,0.898510242,0.879888268
+PhoneHeartbeatSound,,0.650732601,0.645787546,0.668681319,0.662271062,0.652564103,0.636630037,0.640842491,0.638095238
+PickupGestureWiimoteZ_eq,,0.846666667,0.784,0.822,0.817333333,0.798,0.774,0.820666667,0.809333333
+ShakeGestureWiimoteZ_eq,,0.928666667,0.931333333,0.937333333,0.855333333,0.904666667,0.859333333,0.927333333,0.897333333
+SharePriceIncrease,,0.664768806,0.686197378,0.660248447,0.690131125,0.694375431,0.652622498,0.686162871,0.691269841
+Tools,,0.865174129,0.884328358,0.862686567,0.809950249,0.869900498,0.855223881,0.882587065,0.767412935

tsml_eval/publications/y2023/tsc_bakeoff/tsc_bakeoff_2023.ipynb

@@ -15,6 +15,10 @@
     "\n",
     "Our results files are stored [here](https://github.com/time-series-machine-learning/tsml-eval/tree/main/tsml_eval/publications/y2023/tsc_bakeoff/results).\n",
     "\n",
+    "> __Correction:__   \n",
+    "The datasets _Covid3Month_disc_, _FloodModeling1_disc_, _FloodModeling2_disc_ and _FloodModeling3_disc_ have been fixed since the original pre-print. Unfortunately _Table 1_ and _Table C4_ retain some values from the previous versions of these datasets.    \n",
+    "The correct test set sizes are _61_, _202_, _201_ and _184_ respectively for _Table 1_, and the correct accuracy values for _Table C4_ can be found [here](https://github.com/time-series-machine-learning/tsml-eval/tree/main/tsml_eval/publications/y2023/tsc_bakeoff/results/table_c4.csv). Please use the updated datasets and results in any paper sourcing results from this publication.   \n",
+    "\n",
     "## Datasets\n",
     "\n",
     "The 112 UCR archive datasets are available at the [timeseriesclassification.com datasets page](http://www.timeseriesclassification.com/dataset.php).\n",