id: 05773192
dt: j
an: 05773192
au: Wei, Quanling; Yan, Hong
ti: A data envelopment analysis (DEA) evaluation method based on sample
    decision making units.
so: Int. J. Inf. Technol. Decis. Mak. 9, No. 4, 601-624 (2010).
py: 2010
pu: World Scientific, Singapore
la: EN
cc: 
ut: data envelopment analysis; data mining; production possibility set;
    intersection form
ci: 
li: doi:10.1142/S021962201000397X
ab: Summary: Most of evaluation methods on a large number of candidates are
    based a single criterion. To bring the multiple attribute evaluation
    method Data Envelopment Analysis (DEA) into evaluating large number of
    elements, it needs to set up the performance standards and an
    evaluation procedure by the DEA model. In this paper, we first
    determine a set of “standard” candidates, called decision making
    units (DMUs) in the DEA terminology. This standard set is called
    “training set”. We then establish the evaluation procedure based on
    this “training set” for measuring a large number of DMUs. We first
    investigate the efficiency evaluation of a new DMU along with the
    original definition based on the sum formed production possibility set
    which is formed by the $n$ DMUs in the training set and the new DMU. We
    then identify the intersection form of the production possibility set
    formed only by the $n$ DMUs from the training set and show that the new
    DMU evaluation is easy to check if the DMU satisfies a set of linear
    inequalities. The intersection form production possibility set formed
    by the $n$ DMUs from the training set is fixed for evaluating any new
    DMU. Therefore, it provides an efficient and effective method for
    dealing with a large amount of data. The method can be regarded as a
    complementary approach for data mining.
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