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萨默维尔幸福调查数据集

萨默维尔幸福调查数据集

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Life Classification

Waldemar W. Koczkodaj, wkoczkodaj@gmail, independent researcher.Data Set Information:It is a case of supervised learning......

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    README.md

    Waldemar W. Koczkodaj, wkoczkodaj@gmail, independent researcher.


    Data Set Information:

    It is a case of supervised learning with the use of Receiver Operating Characteristic (ROC) to select the minimal set of attributes preserving or increasing predictability of the data.


    Attribute Information:

    D = decision attribute (D) with values 0 (unhappy) and 1 (happy)
    X1 = the availability of information about the city services
    X2 = the cost of housing
    X3 = the overall quality of public schools
    X4 = your trust in the local police
    X5 = the maintenance of streets and sidewalks
    X6 = the availability of social community events

    Attributes X1 to X6 have values 1 to 5.


    Relevant Papers:

    Koczkodaj, W.W.; Li, F.; Wolny-Dominiak, A., RatingScaleReduction package: stepwise rating scale item reduction without predictability loss, R JOURNAL, 10(1): 43-55, 2018.

    W.W. Koczkodaj, T. Kakiashvili, A. Szymanska, J. Montero-Marin, R. Araya, J. Garcia-Campayo, K. Rutkowski, D. Strzalka, How to reduce the number of rating scale items without predictability loss? Scientometrics, 111(2): 581-593, 2017.

    Project R package: [Web link]



    Citation Request:

    For the method:
    W.W. Koczkodaj, T. Kakiashvili, A. Szymanska, J. Montero-Marin, R. Araya, J. Garcia-Campayo, K. Rutkowski, D. Strzalka, How to reduce the number of rating scale items without predictability loss? Scientometrics, 111(2): 581-593, 2017.

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