Given the following dataset:Example Sound FurExample #1 MeowExample #2 BarkExample #3 BarkExample #4 BarkExample #5 MeowExample #6 MeowExample #7 BarkFineExample #8 Meow FineWrite a python code using Naive Bayes to classify the following new example: (Sound=Bark ^ Fur-Coarse ^ Color=Brown).BrownColor ClassCoarse Brown DogFineDogDogDogCatCoarse BlackCoarse BlackFineBrownCoarse BlackCatBlackCatBrown Cat▬▬▬▬▬▬▬▬▬H

Given the following dataset: Example Sound Fur Meow Example #1 Example #2 Bark Example #3 Bark Example #4 Bark Example # 5 Example #6 Coarse Fine Color Class Brown Dog Brown Dog Dog Coarse Black Meow Meow Example #7 Bark Fine Example #8 Meow Fine Coarse Black Fine Brown Coarse Black Dog Cat Cat Black Cat Brown Cat

Given the following dataset: Example Sound Fur Meow Example #1 Example #2 Bark Example #3 Bark Example #4 Bark Example # 5 Example #6 Coarse Fine Color Class Brown Dog Brown Dog Dog Coarse Black Meow Meow Example #7 Bark Fine Example #8 Meow Fine Coarse Black Fine Brown Coarse Black Dog Cat Cat Black Cat Brown Cat

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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A spell checker in a word processing program makes suggestions when it finds a word not in the dictionary. To determine what words to suggest, it tries to find similar words. One measure of word similarity is the Levenshtein distance, which measures the number of substitutions, additions, or deletions that are required to change one word into another. For example, the words spit and spot are a distance of 1 apart; changing spit to spot requires one substitution (i for o). Likewise, spit is distance 1 from pit since the change requires one deletion (the s). The word spite is also distance 1 from spit since it requires one addition (the e). The word soot is distance 2 from spit since two substitutions would be required. a. Create a graph using words as vertices, and edges connecting words with a Levenshtein distance of 1. Use the misspelled word “moke” as the center, and try to find at least 10 connected dictionary words. How might a spell checker use this graph? b. Improve the method…
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Given L = {w = {a, b}*: |w| is even}, the correct statements are: (aa U ab Uba U bb)* is a regular expression that generates L. (ab Uba)* is a regular expression that generates L. aa U ab U ba U bb is a regular expression that generates L. ab U ba is a regular expression that generates L.
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code in java pls Summary: Given integer values for red, green, and blue, subtract the gray from each value. Computers represent color by combining the sub-colors red, green, and blue (rgb). Each sub-color's value can range from 0 to 255. Thus (255, 0, 0) is bright red, (130, 0, 130) is a medium purple, (0, 0, 0) is black, (255, 255, 255) is white, and (40, 40, 40) is a dark gray. (130, 50, 130) is a faded purple, due to the (50, 50, 50) gray part. (In other words, equal amounts of red, green, blue yield gray). Given values for red, green, and blue, remove the gray part. Ex: If the input is: 130 50 130 the output is: 80 0 80 Find the smallest value, and then subtract it from all three values, thus removing the gray.
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