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A database has ten transactions. Let minmum support = 30% and minimum Cofidence = 70%
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
14
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93k
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A database has five transactions. Let min-support = 60_ and min- confidence = 80%. Find all frequent item sets by using Apriori Algorithm T_ID is the transaction ID
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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Consider the following database with minimum support count=60%. Find all frequent item set using Apriori and also generate strong association roles if minimum confidence = 50%.
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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A database has four transitions. Let minimum support and confidence is 50%
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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17k
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How FP tree is better than Apriori Algorithm?
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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1
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11k
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Write short note: FP tree
data warehouse and mining updated 6.1 years ago by parviagrawal100 • 0
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1
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11k
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1
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Define the following terms with example.
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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6.0k
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Discuss Association Rule Mining and Apriori Algorithm.
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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1
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4.1k
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Discuss Association Rule Mining and Apriori Algorithm. Apply AR Mining to find all frequent item sets and association rules for the following dataset: Minimum Support Count = 2 Minimum Confidence = 70
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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Explain constraint based association Rule mining.
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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Explain Multilevel association rules
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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Define linear, non-linear and multiple regressions. Plan a regression model for Disease development with respect to change in weather parameter
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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7.5k
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What are issues regarding classification? Differentiate between classification and prediction.
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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Why is tree pruning useful in decision tree induction.
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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5.2k
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Write Short Note On : Decision Tree based Classification Approach
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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5.0k
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1
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A simple example from the stock market involving only discrete ranges has profit as categorical attribute, with values (Up, Down) and the training data set is given below.apply decision tree algorithm
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
0
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1
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2.2k
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Using table in Appendix C, Create classification model using decision-tree and hence classify following tuple. Very High, Old?
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
2
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1
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11k
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Apply the Naive Bayes classifier algorithm for buys computer classification
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
11
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35k
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Why naive Bayesian classification is called naive. Briefly outline the major ideas of naive Bayesian classification
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
3
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10k
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Apply Bayesian classification to predict class of new tuple (Nicole, Female, 1.67m) Use the following data.
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
2
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1
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12k
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Write short note on: Bayesian classification.
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
3
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1
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22k
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Short note on Issues in classification and explain any one technique of classification.
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
6
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1
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27k
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1
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Discuss different steps involved in Data Preprocessing.
data warehouse and mining updated 6.1 years ago by parviagrawal100 • 0
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42k
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What is noisy data? How to handle noisy data
data warehouse and mining updated 6.1 years ago by parviagrawal100 • 0
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6.5k
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1
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Explain data discretization and summarization
data warehouse and mining updated 6.1 years ago by teamques10 ★ 70k
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