Acronym: LPSType: IntervalsYear: 2015Publication: DAMI

Description: LPS was developed by the same research group as TSF and TSBF at Arizona State University. It is also based on intervals, but the main difference is that subseries become attributes rather than cases. Like TSBF, building the final model involves first building an internal predictive model. However, LPS creates an internal regression model rather than a classification model. The internal model is designed to detect correlations between subseries, and in this sense is an approximation of an autocorellation function. LPS selects random subseries. For each location, the subseries in the original data are concatenated to form a new attribute. The internal model selects a random attribute as the response variable then constructs a regression tree. A collection of these regression trees are processed to form a new set of instances based on the counts of the number of subseries at each leaf node of each tree. Algorithm 8 describes the process.
Source Code: Learned Pattern Similarity Code
Published Results:Recreated Results:

This algorithm doesn't have any published results.

Recreated
Dataset:Result:
Adiac0.7650
ArrowHead0.8063
Beef0.5197
BeetleFly0.8925
BirdChicken0.8540
Car0.8358
CBF0.9845
ChlorineConcentration0.6416
CinCECGtorso0.7428
Coffee0.9500
Computers0.7260
CricketX0.6960
CricketY0.7062
CricketZ0.7136
DiatomSizeReduction0.9145
DistalPhalanxOutlineCorrect0.7674
DistalPhalanxOutlineAgeGroup0.7415
DistalPhalanxTW0.6183
Earthquakes0.6678
ECG2000.8075
ECG50000.9173
ECGFiveDays0.8395
ElectricDevices0.8532
FaceAll0.9615
FaceFour0.8889
FacesUCR0.9100
FiftyWords0.7762
Fish0.9117
FordA0.8695
FordB0.8523
GunPoint0.9719
Ham0.6850
HandOutlines0.8675
Haptics0.4152
Herring0.5486
InlineSkate0.4487
InsectWingbeatSound0.5191
ItalyPowerDemand0.9140
LargeKitchenAppliances0.6797
Lightning20.7566
Lightning70.6308
Mallat0.9082
Meat0.9680
MedicalImages0.7099
MiddlePhalanxOutlineCorrect0.7702
MiddlePhalanxOutlineAgeGroup0.5967
MiddlePhalanxTW0.5032
MoteStrain0.9165
NonInvasiveFatalECGThorax10.8069
NonInvasiveFatalECGThorax20.8259
OliveOil0.8917
OSULeaf0.7635
PhalangesOutlinesCorrect0.7896
Phoneme0.2449
Plane0.9995
ProximalPhalanxOutlineCorrect0.8505
ProximalPhalanxOutlineAgeGroup0.7997
ProximalPhalanxTW0.7222
RefrigerationDevices0.6755
ScreenType0.5059
ShapeletSim0.8742
ShapesAll0.8845
SmallKitchenAppliances0.7237
SonyAIBORobotSurface10.8418
SonyAIBORobotSurface20.8510
StarlightCurves0.9683
Strawberry0.9635
SwedishLeaf0.9256
Symbols0.9598
SyntheticControl0.9716
ToeSegmentation10.8412
ToeSegmentation20.9264
Trace0.9665
TwoLeadECG0.9279
TwoPatterns0.9669
UWaveGestureLibraryX0.8187
UWaveGestureLibraryY0.7527
UWaveGestureLibraryZ0.7665
UWaveGestureLibraryAll0.9677
Wafer0.9951
Wine0.8843
WordSynonyms0.7281
Worms0.6416
WormsTwoClass0.7426
Yoga0.8737

Algorithm: