Influencia de diferentes concentraciones de 2,4-D en la formación de

Following the same steps used for the

α

band the FDR values of the dierent network metris obtained from the max and min synhrostates are arranged

the dierent lassiers as depited in gures 6.18 to 6.20. The same number

of ases are studied for the

β

band, starting from ase I, where all available features are inluded (gure6.18). Onlymetrisof the max synhrostates are

onsidered forase II (gure6.19) andonlymeasures of minsynhrostates for

ase III (gure 6.20).

Figure 6.18: Grouped featuresby theirFDRvaluesordered in dereasingorderfor aseI,

allnetworkmeasuresareonsidered,and

β

band.

The number of groups formed for ase I is eight, one less than for the

α

band, as an be seen in gure 6.18. The rst four groups are formed by a

single feature: CPL max, diameter(D) max, transitivity (T) min and T max

respetively. The suessive groups are formed by 6, 8, 13 and all possible

features respetively. Similarto the previoussetion, the top two features are

fromthemaxsynhrostate set ofmetris. Inaddition,itisnotieablethatthe

FDR values are onsiderably lower than in the

α

band whih means that the power of disrimination of the

β

band is in general, worse than that of the

α

band.

Figure6.19: GroupedfeaturesbytheirFDRvaluesorderedin dereasingorderforaseII,

For ase II the number of groups has inreased from six in the

α

band to seven in the

β

band as illustrated in gure 6.19. The rst three groups are formed of only one feature, with the same features as in ase I: CPL max, D

max and T max. The subsequent subgroups are formed by 5, 6, 8 and the

whole set of features respetively. Figure 6.20 shows the last situation, ase

III. The number of groups resulting in ase III is only four: 1, 3, 5 and all

features respetively. SimilartoaseIII of

α

theband, the FDRvalues inthis senarioare signiantlylowerthan for ase II and ase I.

Figure6.20: GroupedfeaturesbytheirFDRvaluesorderedindereasingorderforaseIII,

onlyminsynhrostatenetworkmeasuresareonsidered,andthe

β

band.

Figures 6.21 and 6.22 show the lassiation performane rates for ase I

and aseIIand IIIrespetivelyforthe 4-tasks lassiationproblem. Forase

I, the highestaveraged auray for both lassiers is obtained with only one

feature, the one presenting the largest FDR value, CPL max. The auray

rate is 73% with true positive rates of 100%, 70%, 70% and 52% for R hand,

non-task, L hand and feet respetively for the linear disriminant algorithm

and 82.5% (100%, 100%, 50%, 80%) for the quadrati disriminant lassier.

This performane is substantially lower than in the same ase for the

α

band where theaveraged auraywasover90%. This behaviourisin linewith the

lower FDR values for this frequeny band as ommented beforehand.

In addition, the true positive rates for both lassiers are learly unbal-

aned. Both algorithms show strength in deteting some tasks espeially R

hand movement with 100% of hits, but are really bad for others suh as feet

or L hand movements with rates near the hane level. It an be seen that

the over-ttingphenomenonis morepronounedinthis ase thaninthe same

senario of the

α

band. For both lassiers the performane drops to 50% or less whenmore than 9 features are used.

Figure 6.21: Comparison of the performane of the toptwo lassiers for ase I in the

β

band. Featuresgroupedaordingto theirFDRvaluearefed tothedierentlassiation

algorithms. Foreah one of the formed subsets, the average auray (a) and the true

positive(TP) foreahoneofthefourtasks(Rhand,relaxingorno-task,Lhand andfeet)

areillustrated. Theuppergraphshowstheperformaneresultsfor thelineardisriminant

analysis lassier(ld)and thebottomgraphshowstheresultsobtainedforthequadrati

disriminantlassier(qd).

For ase II, illustrated in the left row of gure 6.22, the rst two groups

are formedby thesame featuresthanforase I,onsequentlythe performane

of the lassiers is the same as in ase I, 73% and 82.5% for linear and quad-

rati algorithms respetively. The seond lassier, quadrati disriminant,

shows slightly higher averaged auraies in general than linear disriminant

algorithm,with the exeption of the last group. When all of the features are

anyfeaturebutfeetmovementwhihrevealsatruepositiverateof100%. Sim-

ilartotheotherasesstudiedsofarthetwotasksobtaininglowerlassiation

performane are, in general, the neutral fae linked to the non-task or relax

situationand the movementof the feet.

Figure6.22: ComparisonoftheperformaneofthetoptwolassiersforaseII(leftolumn)

andaseIII(rightolumn)in the

β

band. FeaturesgroupedaordingtotheirFDR value are fed to the dierent lassiation algorithms. For eah one of the formed subsets, the

averageauray (a) andthe truepositive (TP) foreahoneof thefour tasks(R hand,

relaxingorno-task,Lhandandfeet)areillustrated. Theupperrowshowstheperformane

results for the linear disriminant analysis lassier (ld) and the bottom row shows the

resultsobtainedforthequadratidisriminantlassier (qd).

Finally,ase IIIpresents the slightlylowerperformanethan inase II and

ase I, with 71% of the averaged auray for both lassiation algorithms.

Similar to ase I and II the true positive rates for the dierent tasks are un-

balaned. Butinthis ase the performane isextremely poorfor thenon-task

senario. Theseresultsanbeexplainedby thefatthatthesynhrostates are

task and frequeny spei ashas been demonstrated earlierin this thesis. In

addition,theonnetivity plotsand onsequently, onnetivity measures show

lear dierenes aross states and frequenies. This means that they proess

dierent information, for example the minimum number of ourrenes state

performs a more speialised proessing, leading to a dierent lassiation

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