Table 4 Classification algorithms and parameter values
From: Multi-sensor fusion based on multiple classifier systems for human activity identification
Classification algorithm | Parameters |
|---|---|
Support vector machine | batchSize=100;buildCalibrationModels=False;c=1.0;calibrator=Logistic-R 1.0E-8-M-1-num-decimal-places 4;checksTurnedOff=False; debug=False;doNotCheckCapabilities=False;epsilon=1.0E-12;filterType=Normalize;kernel=PolyKernel-E 1.0-C 250007; numDecimalPlaces=2;numFolds=-1;randomSeed=1;toleranceParameter=0.001 |
k-Nearest Neighbors | KNN=10;batchSize=100;crossValidate=False;debug=False;distanceWeighing=No distance weighing;doNotCheckCapabilities=False;meanSquared=false;nearestNeighbourSearchAlgorithm=LinearNNSearch;numDecimalPlaces=2;windowSize=0 Standard |
Decision tree (J48) | batchsize=100;binarysplits=false;collapseTree=True;confidenceFactor=0.25; debug=false;doNotCheckCapabilities=false;doNotMakeSplitPointActualValue=false; minNumObj=2;numDecimalPlaces=2;numFolds=3;reduceErrorPrunning=false;saveInstanceData=false; seed=1;subtreeRaising=True; unpruned=false;useLaplace=false;useMDLcorrection=true |
Logistic regression | batchSize=100;debug=false;doNotCheckCapabilities=false;maxit=-1;numDecimalPlaces=4; ridge=1.0E-8;useConjugateGradientDescent=false |