This informational collection is utilized to anticipate the odds of an event of heart assault for a patient. In the season of cutting edge smartphones contributing 12 attributes is not feasible. We play out the product metric examination on the given informational collection. In view of the investigation of information we try to bring the total number of attributes into a small figure and in the end, we may be able to choose which property can be considered and which characteristic can be disregarded.


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    Title :

    Decision making system using machine learning and Pearson for heart attack


    Contributors:


    Publication date :

    2017-04-01


    Size :

    252725 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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