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glory gerald

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About glory gerald

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  • Name
    Glory Carolin Gerald
  • Company
    Northern Trust
  • Designation
    Senior Consultant

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  1. Introduction : In Machine Learning it has become a very common practice to test various models to find a better performing model. The resultant improvement score from these models is sometimes challenging to differentiate if the relationship in the data is captured better or we are just overfitting the data. Hence Validation techniques are used to help us to get out of this dilemma, and the same is more helpful in achieving generalized relationships. What is Model Cross Validation ? Cross Validation is a technique where a particular data set is reserved as a sample on which yo
  2. 'Mizusumashi' is a Japanese term for 'Waterspider'. Waterspider is an aquatic animal that moves in the water quickly changing its direction as required. The behavior of a Waterspider is adapted and is a common practice in manufacturing industries. Thus Implementing a water spider is a great way to put the value and principles of Lean Manufacturing into practice. Manufacturing Industries create a role called as Waterspider whose main job responsibility is to ensure all materials are supplied to where they are needed. The main objective is to have other workers de
  3. FMEA RPN (Risk Priority Number) is the product of Severity, Occurrence and Detection that is used to assess the risk priority level of a failure mode in an FMEA analysis. Severity Rating defines the seriousness of the effect where a numerical rating of the impact on a customers are provided by the FMEA Team(Cross Functional Team)- here, when multiple effects exist for a given failure mode, enter the worst case severity on the worksheet to calculate risk. (Sample scaling: Rated on a scale of 1-10, where 1 = not severe, 10= very severe) Occurrence Rating defines an estimated number of
  4. Class Imbalance is a problem that usually occurs in machine learning algorithms where the occurrence of one of the classes of data is very high compared to other classes present. Here the algorithm will be more biased towards predicting the majority class as there is no enough data to learn the patterns present in the minority class. For better understanding, I have explained the concept through a simple example below, that will also give a brief on how Class Imbalance impacts the outcome of a classification predictive model. Lets consider you have shifted from your hom
  5. Two Sample T Tests are statistical tests that are used to compare the mean values of two independent samples/groups to determine if there is a significant difference between the means of 2 samples in reference. Two samples are considered to be independent if the selection of individuals/objects of one sample does not influence the selection of individuals/objects in the other sample in any way. The data from both samples should be normally distributed to apply the Two Sample T Test. On the other hand, a Paired T Test is a statistical test that is used to compare the mean values of
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