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Application of Data Mining Technology in the Research of Harmaceutical Experiment

Author: LinJuan
Tutor: LiuGang
School: Hunan Normal University
Course: Applied Computer Technology
Keywords: Data Mining Data cube Regression model Partial differential analysis Residuals Optimal reference solution
CLC: TP311.13
Type: Master's thesis
Year: 2009
Downloads: 45
Quote: 0
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Abstract


The purpose of data mining is to find people interested in the hidden, previously unknown knowledge from a large number of databases. Often in practice in order to examine the association between an effect with some factors related to the measurement experiment, some discrete effect analysis of the data, then these discrete effect relationship between the data and the measurement factors will be a very important work. In pharmaceutical experiments tested by experiment, can be some discrete experimental data, these experimental data in a variety of factors (such as the drug concentration, drug works desired temperature, drug works required the immersion time, etc.) under the joint action resulting the effect of the data. These effects data hidden association rules, if only by virtue of prior knowledge and experience of the people can not be found. This paper attempts to data mining techniques applied to this type of data to find useful information implied, to provide scientific and theoretical basis for pharmaceutical research and development. The main methods of data mining database is a multidimensional data analysis that OLAP methods OLAP cube structure can take a variety of technical data, the use of technology is sliced, diced, rotation, drill and roll. However, the data processing of these technologies will produce some one-sidedness. On each subset of data in the slices after treatment with the regression analysis to establish a model of the correlation function, units to a slicing factors partial differential coefficients of the variable factors in the model of each group for all function model packet comprehensive excavation, thus eliminating slicing one-sidedness. In this paper, the practical requirements and to deal with the characteristics of the object, the high-dimensional data mining models. The effects of drugs on the discrete data preprocessing slicing technology through the application of multi-dimensional data analysis, take a multi-factor model, different values ??under the effective correlation function models on the subset of data drawn each slice of factors. Partial differential effect of each variable factors in the model group each slice factors analysis reveals the overall variation of the various factors in the process of a pharmaceutical effect implied mining data analysis of partial differential effect The one-sidedness of the technology useful information at the same time eliminating the slicing process. According to the mining results, combined with the practical constraints, the optimal reference solution obtained in practice, very consistent effects of experimental data in the reference solution with the pharmaceutical R \u0026 D process, has been the recognition of the pharmaceutical R \u0026 D staff.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
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