From Table 1, we can find that: Results of all the classification methods with feature selection and extraction like PLSSVM, GAPLSSVM, PCASVM, GAPCASVM, GAPPSVM are better than that of SVM without any dimension reduction on average.
The average error rates and the corresponding standard deviation values are shown in Table 3, from which we can find the similar observations: Results of all the classification methods with feature selection and extraction like PLSKNN, GAPLSKNN, PCAKNN, GAPCAKNN, GAPPKNN are better than that of KNN without any other dimension reduction on average and on each cases.
For the raw data alone, errors in the X-dimension were on average 20.18 ± 0.86 bins, considerably greater than in the Y-dimension at 8.57 ± 0.51 bins [ t225 = 11.30 P < 0.0001], as would be expected given the high degree of field repetition across compartments and the consequent ambiguity about where the rat was.
Relatively high ME for the intercusp distances may be due to the small magnitude of these dimensions (∼2 9 mm on average) relative to measurement repeatability (standard error of measurement ∼0.20 mm), low variation among individuals due to the functional constraints of precise occlusion, and subjectivity in locating the position of cusp tips.
A dimension on which the average respondent in an occupation scores higher than another dimension can be regarded as more important (at a more sophisticated level) to the occupation.
Tumors reached 20 mm in one dimension on day 18, with an average size over 2000 mm.
When tumors reached 2 cm in any dimension (HCI-002 after HCI-002 aftererage, HCI-009 and HCI-010—12 weeks), mice were killed, and tumon average isolated from the 4R gland, and NCT from the 4L gland, and flasHCI-010 12n HCI-010 12rogen.
From this figure, it can be clearly observed that the multichannel reference spectra exhibit even higher levels of sparsity when analyzed across multiple dimensions, with Gini indices on average above 0.85.
*- average dimension on sick side expressed in % in relation to healthy side (100%).
The ANSYS-PDS & CARES/Life simulation correlated better to the elliptical-hole specimen data than CARES/Life predictions based on average specimen dimensions.
