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Cara Smith

Cara S.

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Breanna Ollech verified

Numerade educator

Discount Rate 10% Data For Plan A: In-House Development Year 0 Year 1 Costs: Consultant time to develop system 16800 0 Purchase necessary software platform 2500 0 Hardware 12500 0 Consultant training time 4500 0 Office staff maintenance, backup and updating 1560 3120 Total Costs: $37,860.00 Present Value Factor (10%) 1.000 0.909 Present Value Benefits: Eliminate overtime 3510 7020 Eliminate additional position 15600 31200 Eliminate daily errors 1560 3120 Total Benefits: $20,670.00 Present Value Factor (10%) 1.000 0.909 Present Value NPV (Net Present Value) PV benefits - PV costs Cash Flow ROI = (Total Benefits - Total Costs) / Total Costs

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Given the query: “What are the total purchases of TV in each consumer-city from suppliers in Chicago?” Which of the following OLAP operations need to be applied in order to solve the query when applied to the (supplier-city, consumer-city, product) cuboid? a) Reduction of dimension product b) Hierarchy climbing on the supplier dimension c) Dice by product name is TV and supplier city is Chicago d) Hierarchy climbing on the consumer dimension e) Reduction of dimension supplier f) Slice by supplier city g) Reduction of dimension consumer

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Consider a cube defined on the following dimension hierarchies and then answer the three questions related to it: {customer < customer_city < customer_state} {supplier < supplier_city < supplier_state} {product < product_group}. Which of the following is a valid cuboid in this cube? select all that apply___ a) (customer_state, supplier, supplier_state, product_group) b) (customer_state) c) (customer, supplier, product) d) (customer_state, supplier, supplier_state) e) (customer_state, supplier, product_group) f) (product, product_group)

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Consider a cube defined on the following dimension hierarchies and then answer the three questions related to it: {customer < customer_city < customer_state} {supplier < supplier_city < supplier_state} {product < product_group}. he number of cuboids that include the customer_city attribute is ______. a) 12 b) 4 c) 18 d) 6

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given the query: “What are the totals sells of auto by supplier-city to consumers in Chicago?” Which of the following OLAP operations need to be applied in order to solve the query when only the raw data is available (base cuboid)? Choose all that apply: a) Reduction of the product dimension b) Hierarchy climbing on the supplier dimension c) Dice by product name is auto and consumer city is Chicago d) Hierarchy climbing on the consumer dimension e) Reduction of the supplier dimension f) Slice by supplier city g) Reduction of the consumer dimension

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Jennifer Stoner verified

Numerade educator

Given the query: “What are the totals sells of auto by supplier-city to consumers in Chicago?” Which of the candidate cuboids below is best fit to efficiently compute the query? a. (supplier-city, consumer-city) b. (supplier-city, consumer-city, product) c. (supplier-city, consumer, product) d. (supplier, consumer, product)

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James Kiss verified

Numerade educator

Which of the following statements relative to rule pruning is true? a) Rule pruning removes rules that are below a given limit of the rule quality measures. b) Rule pruning may improve a rule-based classifier by improving the fitting of the rule to the training set. c) The quality of the pruned rule is measured against the training set. d) Rule pruning may improve a rule-based classifier by reducing over-fitting to the training set.

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\begin{tabular}{|l|l|l|l|l|} \hline Age & Income & Student & Credit_rating & Buys_computer \\ \hline\( <=30 \) & high & no & fair & no \\ \hline\( <=30 \) & high & no & excellent & no \\ \hline \( 31 . .40 \) & high & no & fair & no \\ \hline\( >40 \) & medium & no & fair & no \\ \hline\( <=30 \) & low & no & fair & no \\ \hline\( >40 \) & high & no & fair & no \\ \hline\( >40 \) & low & yes & fair & no \\ \hline\( >40 \) & low & yes & excellent & yes \\ \hline \( 31 . . .40 \) & high & yes & fair & no \\ \hline \( 31 \ldots 40 \) & low & yes & fair & no \\ \hline\( <=30 \) & medium & no & no & no \\ \hline\( <40 \) & low & yescellent & no \\ \hline \end{tabular}

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Which of the following is a common feature of tree induction algorithms? a) Decision trees are constructed recursively from the root to the leaf nodes. b) On any given path from the root to a leaf node any given attribute has to select at least once. c) Splitting attribute selection is such that it minimizes the size of the partitions created at each node. d) Decision trees are constructed bottom-up from the leaf nodes to the root node.

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Given the training set below: Age Income Student Credit_rating Buys_computer <=30 high no fair no <=30 high no excellent no 31…40 high no fair no >40 medium no fair yes <=30 low no fair yes >40 high no fair no >40 low yes fair yes >40 low yes excellent no 31…40 low yes excellent yes <=30 medium no fair no <=30 low yes fair yes >40 medium yes fair yes <=30 medium yes excellent no 31…40 medium no excellent no 31…40 high yes fair yes >40 medium no excellent yes The information gain for attribute Age is _______. Group of answer choices: a) 0.066, b) 0.933, c) 0.061, d) 1.0, e) 0.939

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