fsSimilarityMatrix | R Documentation |
fsSimilarityMatrix
constructs a square matrix of similarity metric values between MTS feature sets.
Metrics are calculated using fsSimilarity
function with cutting-off feature sets
fsSimilarityMatrix(feature.sets, threshold, method)
feature.sets |
a list of matrixes that contains weights for features, estimated by several feature selection algorithms. |
threshold |
the required sparsity of the resulting feature set |
method |
a similarity metric. Directly passed to |
returns a real-valued square matrix with pairwise similarity metric values of feature sets
fsSimilarity
# Load traffic data data(traffic.mini) # Scaling is sometimes useful for feature selection # Exclude the first column - it contains timestamps data <- scale(traffic.mini$data[,-1]) mIndep<-fsMTS(data, max.lag=3, method="ownlags") mCCF<-fsMTS(data, max.lag=3, method="CCF") mDistance<-fsMTS(data, max.lag=3, method="distance", shortest = traffic.mini$shortest, step = 5) mGLASSO<-fsMTS(data, max.lag=3,method="GLASSO", rho = 0.05) mLARS<-fsMTS(data, max.lag=3,method="LARS") mRF<-fsMTS(data, max.lag=3,method="RF") mMI<-fsMTS(data, max.lag=3,method="MI") mlist <- list(Independent = mIndep, Distance = mDistance, CCF = mCCF, GLASSO = mGLASSO, LARS = mLARS, RF = mRF, MI = mMI) (msimilarity <- fsSimilarityMatrix(mlist,threshold = 0.3, method="Kuncheva"))
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