Which one is not correct about the following rule: bread = milk [support 20%,confidence 30%] a) A support of 20% means that 20% of all the transactions under analysis show that bread and milk are purchased together b) A confidence of 30% means that 60% of the customers who purchased a bread also bought the milk c) milk and bread are purchased with 50% probability d) Support and confidence reflect the coverage and certainty of discovered rules

Which one is not correct about the following rule: bread = milk [support 20%,confidence 30%] a) A support of 20% means that 20% of all the transactions under analysis show that bread and milk are purchased together b) A confidence of 30% means that 60% of the customers who purchased a bread also bought the milk c) milk and bread are purchased with 50% probability d) Support and confidence reflect the coverage and certainty of discovered rules

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

See similar textbooks

Similar questions

In your own words explain why we would want to evaluate all probabilities.
When and why do we use the Proportional, Binomial, and Poisson regression models? How and why do each of these models include degrees of freedom?
Q3:Based on BAN logic, write the required assumptions for Ahmed to believe that Khaled believes the correctness of password.
Solve example
ExcelYou must answer the following question (obviously leaving a trace of the calculations made to answer it): If we start at site 0 (therefore p0=1 and all the others pi=0), after how many steps n the probabilities pin are they all close to the asymptotic probabilities πi at most 0.001, ie |pin-πi|≤ 0.001? To answer this question, follow the following steps (see example in image). To be efficient, consider using incrementing, cell calling, etc.(a) On line 2, enter a step counter starting at step 0.(b) On lines 4 and following, indicate the vectors of probabilities pin, so step 0 corresponds to the initial vector, then in the next column, in the column identified by step 1, the vector of probabilities after a step , etc.(c) On lines 15 and following, check if the distance between pin and πi is smaller; in the step 0 column, line 15, indicate: "=ABS(A4-cell containing π0)<=0.001". Then increment (blocking the addresses to be) to check the distances between each pin. Finally,…
Mention some drawbacks of the Linear Model?
Kevin plans to employ a Boolean operator as he is inclined towards investigating two discrete fields of study. It is imperative for Kevin to utilise the appropriate Boolean operator during the process of conducting a search in order to obtain dependable outcomes.
Use an Euler diagram to determine validity: All professional comedians are funny. Some funny people are math professors. Therefore some professional comedians are math professors.
1-Change this code from Matlab to Phython: * Compute and display initial cost and gradient for regularized logistic regression [cost, grad] = costFunctionReg (initial_theta, x, y, lambda); fprintf ('Cost at initial theta (zeros): %f\n', cost); 28 fprintf ('Expected cost (approx) : 0.693\n'); 29 fprintf('Gradient at initial theta (zeros) - first five values only:\n'); 30 fprintf (' %f \n', grad (1:5)); 31 fprintf ('Expected gradients (approx) fprintf (' 0.0085\n 0.0188\n 0.0001\n 0.0503\n 0.0115\n'); 33 % Compute and display cost and gradient with all-ones theta and lambda = 10 test_theta [cost, grad] = 24 25 26 27 first five values only:\n'); 32 ones (size (X, 2),1); costFunctionReg (test_theta, X, y, 10); 34 35 10): %f\n', cost); 36 fprintf ('\nCost at test theta (with lambda 37 fprintf ('Expected cost (approx) : 3.16\n'); 38 fprintf('Gradient at test theta 39 fprintf (' %f \n', grad (1:5)); fprintf ('Expected gradients (approx) first five values only:\n'); 40 first five values…
Given the following: Facts: K Knowledge Base W&D0 D&N W N&K>D Make Forward Chaining for the above KB with the facts? (show the steps of exceution)
You are building a classification model to predict whether a firm will go bankrupt within the next 5 years. When you collect the data, you find that the number of instances of firms that went bankrupt is smaller than the number of cases of firms that did not go bankrupt. Specifically, only 7% of the firms went bankrupt, while the rest did not go bankrupt. Once you build the classification model, you need to compare performance against a baseline. Which of the following would be an appropriate baseline? O Always predicting that the firm does not go bankrupt O Making a prediction that a firm goes bankrupt with 7% probability O Always predicting that the firm goes bankrupt Making a prediction from the set (bankrupt, not bankrupt) with equal probability
Estimate the running time of an algorithm given by following recurrence relations using master (i) T(n) = 3T(n/2) + n