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- In what way does the process of analytical reasoning depend on data modeling? Is there a process that can be used to figure out the ideal number of observations that should be included into our model?Does having a high bias underfits data and produces a model that is too simple and general, while having a high variance overfits data and produces a model that is too complex and specific?10-fold cross-validation is applied to a dataset containing 150 examples. State (i) the number of models that are trained and evaluated, (ii) the number of examples for training a model, and (iii) the number of examples for testing a model
- The hyper-parameters of a model must NOT be tuned on the test data ( i.e, the data used to evaluate the performance of the final model after selecting the hyper-parameters) Group of answer choices True FalseWhat are some creative ways to use binary variables in model formulation?BDAN 250 Select the answer that best describes an ordinal variable: A categorical variable with categories that cannot be ranked A categorical variable where there is a logical rank-order relationship between the variable responses A continuous variable with categories that cannot be ranked A continuous variable where there is a logical rank-order relationship between the variable responses Numeric values at set/even intervals.
- If all that is known about a variable is its "type," then the information that may be gathered may be insufficient. Each variable is comprised of a number of attributes as well as different sorts of data. Please provide an example of this idea being put into practise to explain how it might be utilised to describe a particular variable.A new representation of the data may be an example of a straightforward data transformation. On the other hand, a data transformation may include an intricate integration strategy that draws on a wide variety of data sources. Should we take this statement seriously and determine whether or not it is true to accept it as true or false?Uncertain data modeling generally refers to tuple-level uncertainty. True or false? A True B False
- Is it feasible to differentiate between a prescriptive model and a descriptive model by analyzing the ways in which they vary from one another?Question # 2: Consider the following data Classification Model where YACT is your actual observation and YPRED is the model prediction value. You have to use the data and find CONFUSION MATRIX, and using confusion matrix compute the value of the following errors: Precision value of each class Recall value of each class F-measure value of each class Model Accuracy Model Precision value Model Recall value Model F-measure value YACT R G B B R G R R G G B B R R G B R B G R B G B R R B B G G G YPRED R R R B B B R R G B B R R G G G B B R R B G B R B G B G R RER modeling is one approach in creating a data model. There are several approaches in creating a data model (bottom up, top down, inside out, and mix). 1. explain each of these approaches!2. Then explain when we use top down, bottom up, inside out and mix? what is the function of each of the approaches?