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Projecting a multi-dimensional dataset onto which vector has the greatest variance?
A. first principal component
B. first eigenvector
C. not enough information given to answer
D. second eigenvector
E. second principal component
You are creating a Classification process where input is the income, education and current debt of a customer, what could be the possible output of this process.
A. Probability of the customer default on loan repayment
B. Percentage of the customer loan repayment capability
C. Percentage of the customer should be given loan or not
D. The output might be a risk class, such as "good", "acceptable", "average", or "unacceptable".
What are the advantages of the mutual information over the Pearson correlation for text classification problems?
A. The mutual information has a meaningful test for statistical significance.
B. The mutual information can signal non-linear relationships between the dependent and independent variables.
C. The mutual information is easier to parallelize.
D. The mutual information doesn't assume that the variables are normally distributed.
In which of the scenario you can use the linear regression model?
A. Predicting Home Price based on the location and house area
B. Predicting demand of the goods and services based on the weather
C. Predicting tumor size reduction based on input as number of radiation treatment
D. Predicting sales of the text book based on the number of students in state
Digit recognition, is an example of.....
A. Classification
B. Clustering
C. Unsupervised learning
D. None of the above