Data Mining

  • data-mining-uts-quizPre UTS quiz for Data Mining300 2. Operational databases are the perfect example for OLTP (Online Transaction Processing) and data warehouses are for OLAP (Online Analytical Processing). This means that while operational databases handles day-to-day operations and are optimized for frequent updates, data warehouses are only limited to the storing large amounts of historical data, are optimized for complex queries, and are used for analysis instead of updates. The data warehouses will store the day-to-day updating data co

knowdledge discovery in databaseskdddata-prepartion data mining pattern-evaluation knowledge-presentation Status: #idea Tags: data-mining References

data-warehousingdata-warehousingOLTP OLAP Status: #idea Tags: data-mining References

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Apriori Algorithm

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Step 1: Count Distinct Items

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Step 2: Identify Association Rules

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FP Growth Algorithm

Step 1: Count Distinct Items

400

Step 2: Rearrange Items based count in descending order

400

Step 3: Make FP Growth Tree

  1. Make Null Root Node
  2. And make children sequentially 400
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Step 4: Make Table

Ending with Paths Count of each item in path Candidate itemset with count Frequent itemset

Examples:

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Step 5: Make association rules

400

hmm

Status: #MOC
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