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en:class-eval_examples
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Section: Numerical classification
Evaluation of classification results
Example 1: Project results onto ordination diagram of unconstrained ordination
library (vegan) vltava.spe <- read.delim ('https://raw.githubusercontent.com/zdealveindy/anadat-r/master/data/vltava-spe.txt', row.names = 1) dist_bc <- vegdist (log1p (vltava.spe), method = 'bray') clus <- hclust (sqrt (dist_bc), method = 'ward.D2') clus.cut <- cutree (clus, k = 5) par (mfrow = c(1,2)) NMDS <- metaMDS (dist_bc) # just to make sure it makes meaningful clusters ordiplot (NMDS, type = 'n', main = 'NMDS ordination diagram (Bray-Curtis distances)') points (NMDS, pch = 16, col = clus.cut) plot (clus, cex = .5) rect.hclust (clus, k = 5, border = 1:5)
Example 2: Using silhouette (library cluster)
Evaluates, if the sample has appropriate group membership. Samples with high s value are well clustered, s value around zero means that the sample is between two clusters, and negative s value means that the sample has been misclassified.
For example, we will use results of beta flexible numerical classification of vltava.spe data (see agnes (library cluster)):
## Example of silhouette function ## Following code is not necessary, if you already used examples above... # library (cluster) # dis <- vegdist (sqrt (vltava.spe), method = 'bray') # percentage cover data are transformed by square root # cluster.flexible <- agnes (x = dis, method = 'flexible', par.method = 0.625) # cluster.flexible.hclust <- as.hclust (cluster.flexible) cl <- cutree (cluster.flexible.hclust, k = 5) si <- silhouette (cl, dis) plot (si) # Group 3 has the highest number of misclassified samples, on the other hand, groups 1, 2 and 5 are well defined.
# Comparison of silhouettes for single linkage, complete average linkage method. # dis <- vegdist (sqrt (vltava.spe), method = 'bray') # percentage cover data are transformed by square root # cluster.single <- hclust (d = dis, method = 'single') # cluster.complete <- hclust (dis, 'complete') # cluster.average <- hclust (dis, 'average') par (mfrow = c(1,3)) plot (silhouette (cutree (cluster.single, k = 5), dis)) plot (silhouette (cutree (cluster.complete, k = 5), dis)) plot (silhouette (cutree (cluster.average, k = 5), dis))
Example 3: Fidelity of species to the cluster
library (indicspecies) # to calculate fidelity library (vegan) vltava.spe <- read.delim ('https://raw.githubusercontent.com/zdealveindy/anadat-r/master/data/vltava-spe.txt', row.names = 1) dist_bc <- vegdist (log1p (vltava.spe), method = 'bray') clus <- hclust (sqrt (dist_bc), method = 'ward.D2') clus.cut <- cutree (clus, k = 5) tab <- multipatt (vltava.spe, cluster = clus.cut, fun = 'r.g') # function 'r' is correlation coefficient (phi coef), g indicates that the groups are standardized per size tab$sign[tab$sign$p.value<0.5,] # this table indicates which species has significant fidelity to which cluster or combination of clusters (fidelity tested by Fisher's test); only significant (P<0.05) species are selected
s.1 s.2 s.3 s.4 s.5 index stat p.value Abiealb23 0 0 0 0 1 5 0.5849757 0.005 Acerpla23 1 0 0 0 0 1 0.3985364 0.005 Acerpse23 0 0 0 1 0 4 0.2718779 0.100 Alnuglu23 0 1 0 0 0 2 0.6521616 0.005 Betupen23 0 0 1 0 1 14 0.3220558 0.035 Coryave23 0 1 0 0 1 12 0.3811221 0.010 Cratspe23 1 0 0 0 0 1 0.2121908 0.425 Euoneur23 0 1 0 0 0 2 0.3687661 0.010 Fagusyl23 0 0 0 1 0 4 0.3120710 0.045 Franaln23 0 0 1 0 0 3 0.3462817 0.040 Fraxexc23 0 1 0 0 0 2 0.2921876 0.050 Junicom23 0 0 1 0 0 3 0.2365250 0.140 Liguvul23 1 0 0 0 0 1 0.4561116 0.005 Lonixyl23 0 0 0 0 1 5 0.3563483 0.030 Piceabi23 0 1 0 0 0 2 0.2213071 0.330 Pinusyl23 0 0 1 0 0 3 0.5231362 0.005 Prunpad23 0 1 0 0 0 2 0.5161221 0.005 Prunspi23 1 0 0 0 0 1 0.2721655 0.125 Pyrupyr23 1 0 0 0 0 1 0.3844645 0.015 Querpet23 1 0 1 0 0 7 0.4093827 0.005 Querrob23 1 0 0 0 0 1 0.2526532 0.165 Reynjap23 0 1 0 0 0 2 0.3429972 0.070 Rhamcat23 1 0 0 0 0 1 0.3487968 0.015 Ribeuva23 1 0 0 0 0 1 0.2721655 0.150 Rosacan23 1 0 0 0 0 1 0.2990890 0.080 Rosapen23 0 1 0 0 0 2 0.2407717 0.480 Rosaspe23 1 0 0 0 0 1 0.2366064 0.110 Rubufru23 0 1 0 0 0 2 0.2740088 0.060 Salifra23 0 1 0 0 0 2 0.4527947 0.010 Salitri23 0 1 0 0 0 2 0.2407717 0.405 Salivim23 0 1 0 0 0 2 0.2407717 0.420 Sambnig23 0 0 0 0 1 5 0.4496048 0.005 Sorbauc23 0 1 1 0 1 23 0.2841786 0.080 Tilicor23 1 1 0 1 0 17 0.3308026 0.050 Tilipla23 1 1 0 1 0 17 0.1986532 0.385 Ulmugla23 0 1 0 0 0 2 0.3147620 0.070 Achimil1 1 0 0 0 0 1 0.3885143 0.020 Achitan1 1 0 0 0 0 1 0.5484085 0.005 Aconlyc1 0 0 0 0 1 5 0.2500000 0.270 Aconvar1 0 1 0 0 0 2 0.3980149 0.005 Actaspi1 0 0 0 0 1 5 0.4167222 0.010 Aegopod1 0 1 0 0 0 2 0.6972693 0.005 Aethcyn1 0 1 0 0 0 2 0.2151214 0.475 Agrocan1 0 1 0 0 0 2 0.2407717 0.420 Agrocap1 1 0 0 0 0 1 0.3219597 0.040 Agrosto1 0 1 0 0 0 2 0.2204466 0.340 ... ... ...
summary (tab) # list of diagnostic species for each cluster (and combination of clusters if these clusters are merged)
Multilevel pattern analysis --------------------------- Association function: r.g Significance level (alpha): 0.05 Total number of species: 274 Selected number of species: 127 Number of species associated to 1 group: 107 Number of species associated to 2 groups: 16 Number of species associated to 3 groups: 4 Number of species associated to 4 groups: 0 List of species associated to each combination: Group 1 #sps. 39 stat p.value Euphcyp1 0.656 0.005 ** Vinchir1 0.616 0.005 ** Camprot1 0.610 0.005 ** Hylomax1 0.599 0.005 ** Poa.nem1 0.587 0.005 ** Achitan1 0.548 0.005 ** Bracpin1 0.544 0.005 ** Anthram1 0.542 0.005 ** Hypeper1 0.539 0.005 ** Polyodo1 0.538 0.005 ** Trifalp1 0.535 0.005 ** Pimpsax1 0.527 0.005 ** Diancar1 0.523 0.005 ** Genitin1 0.521 0.005 ** Allisen1 0.480 0.005 ** Bromben1 0.480 0.010 ** Liguvul23 0.456 0.005 ** Silenut1 0.432 0.005 ** Verocha1 0.399 0.010 ** Acerpla23 0.399 0.005 ** Geniger1 0.398 0.020 * Achimil1 0.389 0.020 * Knauarv1 0.389 0.020 * Salvglu1 0.389 0.015 * Poa.ang1 0.389 0.005 ** Pyrupyr23 0.384 0.015 * Secuvar1 0.381 0.020 * Verbnig1 0.372 0.020 * Carespe1 0.369 0.025 * Galialb1 0.369 0.010 ** Festrub1 0.368 0.020 * Hedehel1 0.365 0.025 * Rhamcat23 0.349 0.015 * Verooff1 0.341 0.030 * Agrocap1 0.322 0.040 * Hierpil1 0.319 0.040 * Festhet1 0.311 0.010 ** Fallcon1 0.304 0.045 * Caremur1 0.289 0.020 * Group 2 #sps. 44 stat p.value Lycoeur1 0.961 0.005 ** Phalaru1 0.868 0.005 ** Festgig1 0.861 0.005 ** Sympoff1 0.768 0.005 ** Stacsyl1 0.722 0.005 ** Calysep1 0.721 0.005 ** Myospal1 0.714 0.005 ** Aegopod1 0.697 0.005 ** Ranurep1 0.675 0.005 ** Alnuglu23 0.652 0.005 ** Stelnem1 0.629 0.005 ** Lysivul1 0.622 0.005 ** Cirsole1 0.596 0.005 ** Angesyl1 0.576 0.005 ** Valeexc1 0.563 0.005 ** Rumeaqu1 0.552 0.005 ** Mentx.v1 0.544 0.005 ** Galiapa1 0.543 0.005 ** Scronod1 0.521 0.005 ** Prunpad23 0.516 0.005 ** Bidefro1 0.509 0.005 ** Soladul1 0.497 0.005 ** Cardper1 0.482 0.005 ** Lythsal1 0.479 0.005 ** Chaehir1 0.477 0.005 ** Artevul1 0.466 0.005 ** Impagla1 0.465 0.005 ** Salifra23 0.453 0.010 ** Myosaqu1 0.441 0.005 ** Urtidio1 0.431 0.005 ** Mentlon1 0.416 0.015 * Carebri1 0.408 0.005 ** Poa.pal1 0.407 0.005 ** Aconvar1 0.398 0.005 ** Cusceur1 0.398 0.015 * Humulup1 0.382 0.005 ** Euoneur23 0.369 0.010 ** Gleched1 0.353 0.025 * Cardama1 0.343 0.040 * Silespe1 0.343 0.040 * Elymcan1 0.342 0.025 * Carebue1 0.336 0.035 * Glycmax1 0.324 0.010 ** Fraxexc23 0.292 0.050 * Group 3 #sps. 6 stat p.value Avenfle1 0.686 0.005 ** Pinusyl23 0.523 0.005 ** Vaccmyr1 0.492 0.005 ** Senevis1 0.393 0.010 ** Hiermur1 0.388 0.020 * Franaln23 0.346 0.040 * Group 4 #sps. 2 stat p.value Chelmaj1 0.480 0.005 ** Fagusyl23 0.312 0.045 * Group 5 #sps. 16 stat p.value Lunared1 0.752 0.005 ** Seneova1 0.715 0.005 ** Cardimp1 0.711 0.005 ** Prenpur1 0.649 0.005 ** Oxalace1 0.644 0.005 ** Mercper1 0.640 0.005 ** Abiealb23 0.585 0.005 ** Impanol1 0.458 0.010 ** Athyfil1 0.453 0.005 ** Sambnig23 0.450 0.005 ** Actaspi1 0.417 0.010 ** Milieff1 0.408 0.005 ** Galemon1 0.405 0.015 * Galiodo1 0.367 0.015 * Lonixyl23 0.356 0.030 * Cardfle1 0.338 0.045 * Group 1+2 #sps. 2 stat p.value Stelhol1 0.505 0.005 ** Lamimac1 0.358 0.020 * Group 1+3 #sps. 6 stat p.value Hiersab1 0.547 0.005 ** Lychvis1 0.482 0.005 ** Hierlac1 0.446 0.005 ** Querpet23 0.409 0.005 ** Cytinig1 0.373 0.015 * Festpal1 0.355 0.010 ** Group 1+4 #sps. 1 stat p.value Clinvul1 0.374 0.015 * Group 2+4 #sps. 1 stat p.value Galespc1 0.358 0.015 * Group 2+5 #sps. 1 stat p.value Coryave23 0.381 0.01 ** Group 3+4 #sps. 1 stat p.value Luzuluz1 0.484 0.005 ** Group 3+5 #sps. 1 stat p.value Betupen23 0.322 0.035 * Group 4+5 #sps. 3 stat p.value Dryofil1 0.410 0.005 ** Moehtri1 0.410 0.015 * Dryocar1 0.342 0.035 * Group 1+2+4 #sps. 1 stat p.value Tilicor23 0.331 0.05 * Group 2+4+5 #sps. 3 stat p.value Asareur1 0.520 0.005 ** Dryodil1 0.469 0.005 ** Melinut1 0.350 0.025 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
en/class-eval_examples.txt · Last modified: 2020/05/14 08:57 by David Zelený
