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jKi-18

jKi-18
Challenge 18: Categorizing NotesLevel: MediumDescription: A common problem in mechanical and medicaldata is associating notes with a category. In this challenge,you will automate the process of sorting mechanical notes intotheir correct category. Here’s an example:INPUT --List of Categories-- 1. Scratch 2. Crack 3. Defect --Notes-- 1. The product was defective. 2. A crack was caused by client. 3. Many scratches noted.OUTPUT Note Category 1. The product was defective. Defect 2. A crack was caused by client. Crack 3. Many scratches noted. ScratchDon't worry about using fancy machine learning or naturallanguage processing models. This problem can be handledreasonably well using a total of 5 nodes (simple solution), anda more refined solution involves just 8 nodes (complexsolution). Also don't worry about getting 100% accuracy. Rule engineapproach Solution using similarity search approach Inspection nodescategoriesNode 3Solution 1-easy-Node 6Node 28Node 30Node 32Node 33Node 34Node 35Node 36Node 37Node 38Node 39Node 40Node 43Node 44Node 45Node 47Node 53Node 54Node 55Solution 2-similarity-Node 57Node 58 Excel Reader Excel Reader String Manipulation Rule Engine(Dictionary) Cell Splitter ExtractColumn Header Table Row ToVariable Loop Start Transpose Column Filter Column Filter Counter Generation Similarity Search Column Rename Column Rename Loop End (ColumnAppend) Joiner Rule Engine RowID Missing Value ConstantValue Column Column Filter Column Filter Column Aggregator Column Rename String Manipulation String Manipulation Challenge 18: Categorizing NotesLevel: MediumDescription: A common problem in mechanical and medicaldata is associating notes with a category. In this challenge,you will automate the process of sorting mechanical notes intotheir correct category. Here’s an example:INPUT --List of Categories-- 1. Scratch 2. Crack 3. Defect --Notes-- 1. The product was defective. 2. A crack was caused by client. 3. Many scratches noted.OUTPUT Note Category 1. The product was defective. Defect 2. A crack was caused by client. Crack 3. Many scratches noted. ScratchDon't worry about using fancy machine learning or naturallanguage processing models. This problem can be handledreasonably well using a total of 5 nodes (simple solution), anda more refined solution involves just 8 nodes (complexsolution). Also don't worry about getting 100% accuracy. Rule engineapproach Solution using similarity search approach Inspection nodescategoriesNode 3Solution 1-easy-Node 6Node 28Node 30Node 32Node 33Node 34Node 35Node 36Node 37Node 38Node 39Node 40Node 43Node 44Node 45Node 47Node 53Node 54Node 55Solution 2-similarity-Node 57Node 58Excel Reader Excel Reader String Manipulation Rule Engine(Dictionary) Cell Splitter ExtractColumn Header Table Row ToVariable Loop Start Transpose Column Filter Column Filter Counter Generation Similarity Search Column Rename Column Rename Loop End (ColumnAppend) Joiner Rule Engine RowID Missing Value ConstantValue Column Column Filter Column Filter Column Aggregator Column Rename String Manipulation String Manipulation

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Created by: franz
Created at: 2022-05-26
On NodePit since: 2022-05-27
Last update: 2024-04-27
Created with KNIME version: v4.5.2
Tags: justknimeit-18

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