Data minig course Given the observation table for student who pass/ do not pass the test according to their studying style, concentration level and sleeping habits below: Draw the decision tree for the below table Test Study Sleep Concentrate Time Pass ? 1 Hard No High Long Yes 2 Less Yes High Less Yes 3 Don’t study No No Long No 4 Don’t study No High Long No 5 Hard Yes No Long Yes 6 Hard No No Less No 7 Less Yes No Long No 8 Less Yes High Long Yes 9 Less Yes No Less No 10 Don’t study No High Less No

Data minig course Given the observation table for student who pass/ do not pass the test according to their studying style, concentration level and sleeping habits below: Draw the decision tree for the below table Test Study Sleep Concentrate Time Pass ? 1 Hard No High Long Yes 2 Less Yes High Less Yes 3 Don’t study No No Long No 4 Don’t study No High Long No 5 Hard Yes No Long Yes 6 Hard No No Less No 7 Less Yes No Long No 8 Less Yes High Long Yes 9 Less Yes No Less No 10 Don’t study No High Less No

New Perspectives on HTML5, CSS3, and JavaScript

6th Edition

ISBN:9781305503922

Author:Patrick M. Carey

Publisher:Patrick M. Carey

Chapter12: Working With Document Nodes And Style Sheets: Creating A Dynamic Document Outline

Section12.2: Visual Overview: Exploring Attribute Nodes

Problem 3QC

See similar textbooks

Similar questions

decision_trees.ipynb Decision trees Step 1: Create a decision tree classifier Now it is time to create a decision tree classifier using entropy: []... Step 2: Train the Classifier on the Training Data: (the arguments are the same as the knn classifier) []..... Parsing clf.fit(iris_features_train, iris_label_train) clf is our decision tree classifier. fit means to train the classifier on the dataset. iris_features_train is the DataFrame containing all the feature columns of the training set and iris_label_train are the labels of the training set.
Data Mining The following is the Training Data which is the result of an average monitoring for 2 weeks of 8 people who are suspected of being infected with the Omicron variant of the Corona virus. Based on the data, make a Decision Tree, using the attribute selection measures "GINI Index". With the class attribute is the column "Infected"
Data Mining a. The following is the Training Data which is the result of an average monitoring for 2 weeks of 8 people who are suspected of being infected with the Omicron variant of the Corona virus. Based on the data, make a Decision Tree, using the attribute selection measures "GINI Index". With the class attribute is the column "Infected". b. Based on the Decision Tree generated in question “a” above, please make Classification Rules.
Horizontal sequence :VIRL Vertical sequence:MKF Scoring rules: g/o = -3, g/e = -1, match or mismatch - from PAM250 substitution matrix below. SW algorithm. 1. Complete the scoring matrix. Scoring matrix with PAM250 scores: V I R L M K F 2. Set up, initialize and complete the SW matrix. 3. Retrace, align and score alignment(s). Use the arrows and circles for the matrix and path(s). V I R L M K F Align and score all optimal alignments here. PLZ the arrows and circles for the matrix and path(s) AND SHOW ALL possible Alignment
Do it correct plz.. Please write business rules er diagram. Don't be wrong sir
Horizontal sequence :VIRL Vertical sequence:MKF Scoring rules: g/o = -3, g/e = -1, match or mismatch - from PAM250 substitution matrix below. NW algorithm. 1. Complete the scoring matrix. Scoring matrix with PAM250 scores: V I R L M K F 2. Set up, initialize and complete the NW matrix. 3. Retrace, align and score alignment(s). Use the arrows and circles for the matrix and path(s). V I R L M K F Align and score all optimal alignments here. PLZ the arrows and circles for the matrix and path(s) AND SHOW ALL possible Alignment
Horizontal sequence :VIRL Vertical sequence:MKF Scoring rules: g/o = -3, g/e = -1, match or mismatch - from PAM250 substitution matrix below. NW algorithm. 1. Complete the scoring matrix. Scoring matrix with PAM250 scores: V I R L M K F 2. Set up, initialize and complete the NW matrix. 3. Retrace, align and score alignment(s). Use the arrows and circles for the matrix and path(s). V I R L M K F Align and score all optimal alignments here.
Data about the horses that have been awarded top places in events has already been captured ina spreadsheet (an extract from the spreadsheet is shown below). The data has been normalised tofirst normal form already – underlined column names indicate composite primary key columns.HorseID Horse Name BreedID Breed Name EventID Event Name Place1 Speedy 1 Thoroughbred 15 Show Jumping 11 Speedy 1 Thoroughbred 2 Dressage 52 Candy Floss 2 Appaloosa 15 Show Jumping 23 Getting Warmer 1 Thoroughbred 2 Dressage 44 Mother’s Love 9 Arabian 3 Eventing 3 Normalise the above data to third normal form (3NF). Show all steps as well as the final…
When creating a decision tree, explain clearly and in detail which questions should be at the top of the hierarchy?
Decision Tree PART I: Using following columns build a model to predict if person would survive or not, • Pclass• Sex• Age• Fare Calculate score of your model (Screen Shot)
Question 4 call simulate_several_key_strikes 5000 times , each time simulating the monkey stringing five consistant keys.Compute the proportion of times the monkey types "Data8" , calling this percentage proportion data_proportion simulate_several_key_strikes.sample(5000)word == "Data8"if (simulate_several_key_strikes == word): data_proportion = word + simulate_several_key_strikes.item(1) data_proportion
Preference Ranking Organisation Method for Enrichment of Evaluations(PROMETHEE)The Promethee methods use pairwise comparisons and outranking relationships tochoose the best alternatives. Since the purpose of this section is to build a rankingof classification algorithms, PROMETHEE II is selected. The PROMETHEE IIprocedure as:

SEE MORE QUESTIONS

Recommended textbooks for you

New Perspectives on HTML5, CSS3, and JavaScript

Computer Science

ISBN:

9781305503922

Author:

Patrick M. Carey

Publisher:

Cengage Learning

New Perspectives on HTML5, CSS3, and JavaScript

Computer Science

ISBN:

9781305503922

Author:

Patrick M. Carey

Publisher:

Cengage Learning

SEE MORE TEXTBOOKS

GET THE APP

About FAQ Academic Integrity Sitemap Document Sitemap

Contact Bartleby Contact Research (Essays)High School Textbooks Literature Guides Concept Explainers by Subject Essay Help Mobile App

GET THE APP

Privacy

Your CA Privacy Rights

Your NV Privacy Rights

About Ads

Manage My Data

bartleby, a Learneo, Inc. business

Test	Study	Sleep	Concentrate	Time	Pass ?
1	Hard	No	High	Long	Yes
2	Less	Yes	High	Less	Yes
3	Don’t study	No	No	Long	No
4	Don’t study	No	High	Long	No
5	Hard	Yes	No	Long	Yes
6	Hard	No	No	Less	No
7	Less	Yes	No	Long	No
8	Less	Yes	High	Long	Yes
9	Less	Yes	No	Less	No
10	Don’t study	No	High	Less	No