Info

Proportion = 0.580718

Source: Refs. 13 and 14.

Source: Refs. 13 and 14.

ences, DA and MRA serve that purpose more admirably. DA is a procedure that depends for its effectiveness on transposing the measurement values in such a way that the linear distance between samples is maximized. There are four kinds of DA: stepwise (SDA), linear or multiple (LDA), canonical, and nearest-neighbor. Normally SDA is used to winnow from the measurements those that are not effective as discriminators, then ferret from among those retained the ones that are most effective. In actuality, computer programs search for the most effective discriminator among the measurements, eg, gas chromatographic peaks, liquid chromatographic peaks, or mechanical measurements. Having selected the best single discriminator, the program then looks for a second measurement to go with the first to form a pair of measurements for discrimination. The process goes on in that fashion until enough measurements have been selected to permit all the samples to be assigned to the proper class, or else the process fails because it runs out of discriminating variables before full resolution of product differences is obtained. Table 5 shows how the process works schematically and Table 6 lists the kind of output obtained. The data are for the classification of a certain industrial produced in four branch plants. The objective was to learn whether the products could be assigned by chemical measurement to the plant where each was actually produced. Sometimes sample differences cannot be resolved by instrumental measurements. Generally where there are many measurements available such as gas chromatographic or liquid chromatographic analysis yields, there is no difficulty in finding sufficient discriminating variables to permit the samples to be correctly classified. When sensory scores for various attributes (such as crumbliness, graininess, sweetness, a sulfidic odor, and a grassy note) are the kinds of quantitative values available, there is generally less success in attaining 100% classification. Sometimes 100% success can be achieved, but usually the maximum is approximately 85%.

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