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Preprocessing technique Classification method Autoscale Weighted autoscale Optimum linear transformation I. Linear classifier a) Least-squares 83/83 83/83 83/83 b) Negative feedback 56/83 77/70 74/87 II. 3-Nearest Neighbor 80/60 89/80 92/97 III. Multiclass classifier a) Least-squares 91/87 91/87 91/87 b) Negative feedback 94/90 93/90 78/90method is invariant to all linear transformations, the results are the same for the three preprocessed sets of mass spectral data.The second classification method used in this study was the K-Nearest Neighbor Classification Rule (4) with K equal to three. This method is a multiclass method that does not depend upon linear separability. Hence, classification performance is improved in the last two sets of preprocessed data. The attributes and limitations of this method can be found in the chemical literature (4).The results of the multiclass classifier ( ) introduced in this paper are also found in Table I. Here again, the least squares procedure (a) and the error correction feedback procedure (b) were used to calculate the necessary weight vectors. The multiclass procedure performed very well. The overall performance indicates that the least squares procedure for calculating the weight vector is best. Again, note that least squares solutions are unique and are invariant to all linear transformations of the data. These attributes recommend the least squares multiclass procedure for applications which involve more than two classes. The method is at least as effective as other linear classifiers and comparable in accuracy to the more expensive K-Nearest Neighbor Rule.

As a result of the rapid increase in requests and the ever-rising backlog of cases, forensic science laboratories are developing an intense interest in analytical procedures that can provide rapid, inexpensive, and sensitive methods for identifying drugs. However, the forensic chemist must always be aware of the scientific accountability that is expected of him or her in our adversary system of justice. The necessity for performing a specific identification far outweighs any shortcuts that may be adopted to expedite a chemical analysis. As the importance of scientific testimony grows, the courts are becoming more conscious of criteria that must be met to support the admissibility of scientific evidence. The accuracy of heretofore accepted statements and descriptions relating to the identification and comparison of physical evidence is increasingly becoming subject to scrutiny and debate. Practitioners of the law are starting to take advantage of inconsistencies in the scientific literature and the lack of experimental data to discredit an entire scheme of analysis. One only has to examine recent court decisions pertaining to the forensic analysis of marihuana to confirm this trend. The contrasting opinions of experts regarding the number of Cannabis species have served to confuse and, in some instances, discredit a botanical and chemical scheme of analysis that until the present has found general acceptanee in the forensic science community [1,2].

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