![]() Summarize aggregate What data type must be assigned to the dependent variable in RapidMiner when building linear regression models? filter examples To calculate the sum total of all predictions in a linear regression operator in RapidMiner, use a(n) _ operator. not statistically significant To remove out-of-range values from a scoring data set in RapidMiner, use a _ operator. intercept coefficient In linear regression, p-values larger than alpha indicate that their corresponding independent variables are _. coefficient In linear regression, the x variable is the independent variable's _ value In linear regression, the b variable is the model's _. The coefficients for each independent variable alpha In linear regression, the m variable is the independent variable's _. true In linear regression, the p-values for each independent variable must be smaller than _. Replace filter examples Value ranges for all attributes for every observation in a scoring data set must be within the value ranges for the corresponding attributes in the training data set in a linear regression model. label To remove unwanted or unusable observations from data sets in RapidMiner, use the _ operator. ![]() Probability variance probability, variance In RapidMiner, the attribute you wish to predict must be set to the role of _. Triangulation triangulation The Naïve Bayes technique for predicting categorical outcomes employs both _ and _. Training scoring Changing one categorical attribute (e.g., "Blue," "Red," "Green") into a series of binary attributes (e.g., Blue = 0/1 Red = 0/1 Green = 0/1) is known as _.ĭummy coding dummy coding Using two or three different modeling techniques on the same data and then comparing predicted outcomes across the different models is called _. Scoring training Data that does not have known outcome values for an attribute you wish to predict is known as _ data. Predict predict & categorize The attribute you want to predict in a predictive model is called a(n) _.Ĭategory variable dependent variable An attribute used to predict outcome values in a predictive model is called a(n) _.Ĭategory variable independent variable Data containing known outcome values for an attribute you wish to predict is known as _ data. ![]() ![]() Discriminant analysis, k-Nearest Neighbors, and Naïve Bayes are all datamining models used to _ data values. ![]()
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