Pattern recognition decision tree

For solving the pattern recognition problem encountered in the operation of chemical processes, the analysis of measured process data and extraction of process trends at multiple scales constitutes the feature extraction, whereas induction via decision trees is used for inductive... 

Yeh and Spiegelman [24], Very good results were also obtained by using simple neural networks of the type described in Section 33.2.9 to derive a decision rule at each branching of the tree [25]. Classification trees have been used relatively rarely in chemometrics, but it seems that in general [26] their performance is comparable to that of the best pattern recognition methods. 

Data, computer versus human view, 56-58 Data sets, see Example data sets DCLS, seeDirea da ical least squares (DCLS) Decision trees defining the problem, 9-11 muiiivaiiate calibration, 186-188 pattern recognition. 62-64 Definitions. 5-7 Degrees of freedom PLS F-test. 304 SLMCA F-test. 152-153 Dendrogram construaion of. 65-71 definition of 65... 

Multivariate data consist of many observations on variables for a large number of samples, such as the determination of metals in batches of honey (55) or wine samples (56) from different regions. It becomes difficult to visually see patterns within the samples so a statistical approach is used to analyze the data. For this type of pattern recognition, it is normally best to follow a decision tree (57). Figure 8.2 shows the decision tree that was followed for pattern recognition within the opium and poppy straw samples. 

FIGURE 8.2. Illustration of the decision tree used for pattern recognition. 

SIMCA and related methods Back propagation neural networks Decision trees Genetic algorithms Pattern recognition in data sets A Overview... 

One of the first pattern recognition applications in mass spectrometry was the attempt to determine the molecular formula by a decision tree C120, 128, 1293. The decision tree contained several binary classifiers. Each of the classifiers decided whether a compound contains more atoms than a given number- A run through the decision tree yields the molecular formula of an unknown whose low resolution mass spectrum is known. A tree with 26 classifiers was necessary for a set of 346 compounds of formulas --i 6 0-3 0-2 spectra with an artifi-... 

Additional application of chemical knowledge to the selection of features or to the classifier construction has improved the classification results C1933. A comparison between pattern recognition methods and a sophisticated interpretative library search system for mass spectra ( STIRS C39, 4221) has indicated some superiority of the STIRS-system C172, 202, 3321. A decision tree pattern recognition was recommended by Neisel et. al. C2051 as a supplement to library search. 

In smnmaty, we have demonstrated that differentiation and imequivocal identification of taxonomically closely related species within B. cereus s.l. by MALDI-TOF MS constitutes a considerable challenge. Although data fi om a number of laboratories have raised reasonable doubts on the validity of originally postulated mass spectral biomarkers for B. anthracis, it has been demonstrated that advanced methods of multivariate pattern recognition such as neinal network analyses (Lasch et al. 2009), or decision-tree techniques optimized on the basis of similarity-grouped reference libraries (Dybwad et al. 2013), represent appropriate data analysis tools... 

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