DQuestion 1 Which of the following is true about independent and dependent varia
ID: 332173 • Letter: D
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DQuestion 1 Which of the following is true about independent and dependent variables? In supervised learning the inputs to predictive models are independent variables and the predicted values are dependent variables. None of these are correct. Dependent variables must be categorical quantities and independent variables may be numerical or categorical quantities. Independent variables must be numerical quantities and dependent variables may be numerical or categorical quantities. In supervised learning the inputs to predictive models are dependent variables and the predicted values are independent variables. DQuestion 2 Which of the following is the most accurate statement about supervised and unsupervised learning? Supervised learning models target variables as functions of predictors; unsupervised learning identifies patterns in data. None of these are correct. For both unsupervised learning and supervised learning we predict a response variable. Both supervised and unsupervised learning partition a data set into a training data set, a validation data set, and optionally, a test data set. In unsupervised learning we partition the data set provided for learning and use one partition to validate the learned model; in supervised learning there is no reason to partition the data set. DQuestion 3 Why did Target want to know if a woman is pregnant, and how did they do this? (Week 3 Discussion article) Target had a large amount of customer data that could be analyzed for signals that a woman is expecting Target believed the right offers at the right time to expectant mothers would induce them to become reliable customers for many years Target understood people's purchasing habits change with major life changes. Target wanted to make product offers of interest to expectant mothers before other retailers could. All of these are correct. Question 4 Which is NOT an example of a business application of supervised learning? Predicting home sales pricesin a neighborhood. Categorizing customers as likely or unlikely to respond to a promotional offer. Identifying products that customers tend to purchase together. All of these are correct. Classifying credit card transactions as valid or fraudulent.Explanation / Answer
Q!. (c) The dependent variable is the categorical quantities and independent variable may be numerical and categorical quantities because independent variable are the Cause Variable on the other hand the dependent variable reprents the effect or response which are in categoical quanties. Ex. Heart rate is Dependent , Stress is Independent Variable.
Q2. (e) In unsupervised learning we partitione the data set provide for learning and use one partitio to validate the learned model and supervised leaning , there is no reason to partition the data set because Supervised is a process of algorithem learning from the dataset , under the guidance of teacher but Unsupervised learning is divided into clustering and association of data.
Q3. E) all the above are correct. Since by regular keeping notice the women purchasing behaviour, the target wanted to sell the expectant women product at the right time to remain loyal to the customer.
Q4. (d) all of the above since supervised data mining pridicts about the data which has two possble outcomes and then classify the data .
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