Match the following pair of term and statement related to Uncertain Reasoning. A height of 1.7m can be represented as Drag answer here 90% tall and 30% very tall. A 60% staff need can be Drag answer here translated to require 45 staffs Given the member-value for location is 0.7 Drag answer here and the size of the unit is 0.3, the chances for the unit to be sold is 0.3. Fuzzy Inferencing Defuzzification Fuzzification

Match the following pair of term and statement related to Uncertain Reasoning. A height of 1.7m can be represented as Drag answer here 90% tall and 30% very tall. A 60% staff need can be Drag answer here translated to require 45 staffs Given the member-value for location is 0.7 Drag answer here and the size of the unit is 0.3, the chances for the unit to be sold is 0.3. Fuzzy Inferencing Defuzzification Fuzzification

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

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Answer the following questions using the output below please be brief. If there are two possibleanswers one will suffice. Where necessary a range analysis must be shown.convert to minutes) a) What is the optimal solution (in words? b) An additional 4 hours of shaper time became available. Evaluate the effect? Explain c) Two hours of Grinder time was lost. Evaluate the effect?
Question 10 Please don't copy past, I have gone through the answers on theInternet but they all are wrong please provide accurate and your own solutionDon't copy past
i tried this, got this result after submitting hw Incorrect result when calling get_stat({'Defense': 219, 'Strength': 143, 'Luck': 2, 'Dexterity': 231, 'Constitution': 10, 'Intelligence': 63, 'Willpower': 102, 'Charisma': 7})returned: nullexpected: 219
Which of the following statements about confusion matrix is wrong A) Confusion matrix is a performance measure for probability prediction techniques B) Confusion matrix is derived based on classification rules with cut-off value 0.5 C) Confusion matrix is derived based on training partition to measure a model’s predictive performance D) None of the above I need typed answer with explanation K
PLEASE ANSWER THEM. JUST GIVE THE OPTIONS! 1- Choose all of the following which is true about confidence of association rules Select one or more: a. Confidence is used to quantify strength of a rule b. Confidence is defined as confidence(A -> B) = P(BIA), = P(A) + P(B) c. Contidence is detined as the probabilitv that B occurs when A occurs d. Contidence is defined as the probability that either A or B occurs e. It is a common practice to favor rules whose confidence is above a threshold value 2- Choose all of the following which is true about the "lift" of association rules Select one or more: a. Lift is an indicator of the strength of an association rule b. Lift is only used to filter unimportant events c lift and support can be used as alternative measures for the same purnose d. Lift and confidence can be used as alternative measures for the same purDose e. Lift is the probability of A and B occurring together divided by their joint probability if they were they were…
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This counts as one of my questions, so I will just ask the question here if you can assist please with the next three. Build a CKY table to parse each sentence below. Also for the 3 invalid sentences below. Go to South Padre Get a hotel On the beach I want a view Love the sunrise A nice vacation Book a boat I love water Need this trip Waves are high Prefer the boat I enjoy speed 3 Invalid Sentences: Like boat to Trip vacation to Hotel want to CFG: S -> NP VP NP -> 'I' | 'Texas' | 'South Padre' | 'hotel' | 'beach' | 'view' | 'sunrise' | 'vacation' | 'boat' | 'water' | 'trip' | 'waves' | 'speed' VP -> 'want' 'to' V | 'like' NP | 'Go' 'to' NP | 'Get' 'a' NP | 'On' 'the' NP | 'Love' 'the' NP | 'Book' 'a' NP | 'Need' 'this' NP | 'Prefer' 'the' NP | 'enjoy' NP V -> 'travel' | 'swim' | 'be' CFG converted into CNF: S → NP VP NP → N1 | N2 | N3 | N4 | N5 | N6 | N7 | N8 | N9 | N10 | N11 | N12 | N13 | N14 VP → V1 VP2 | V2 NP | V3 NP | V4 NP | V5 NP | V6 NP | V7 NP | V8 NP | V9…
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Justify the answer that is agree or disagree.
Question 6 Full explain this question and as per godlines all part work a abd b solution sent me
Question 10 sis Good always tell the truth Bad always lies. use a truth table to determine what type each person is or if their status cannot be determined.A: “I am Good or B is Bad”B: “A is Bad if C is Good”C: “I am Bad or A is Bad only if B is Good" Please show work and address all parts Don't ignore any part all part work u