Chemical Technology, Control and Management


The paper discusses two problem, the firth, possibilities of improving the quality of the recognition algorithm based on partial precedent, by the original pre-training procedures. And second finding the optimal procedure for constructing improved results in some sense, the algorithms for calculating estimates. The peculiarity of this algorithm is that as precedents only such "anchor points" of a pattern that ensuring the following conditions are left: the distance from any point on the training set of i-th pattern to their nearest precedent is less than the distance to the nearest precedent of another pattern. This set of precedents provides unmistakable recognition of all samples of the training set. Thus, the probability of correctly separating of classes increases significantly. The set of dedicated training samples gives a chance to improve the level of reliability of data mining. One of species plant of tulip have chosen as object of research. This process is carried out via morphological features of tulip. The information about tulip is obtained from Central herbarium of institute of Botany of the Uzbek Academy of sciences.

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