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1. Create dockerfile :~/yoon/dockerfile/ 2. Create requirement.txt elasticsearch==7.15.0 pandas==1.2.4 prefixspan==0.5.2 numpy==1.21.3 urllib3==1.26.7 mlxtend==0.19.0 3. Clone my project Local : Edit code → git add . → git commit → git push origin main $ git add . $ git commit -m "modified requirement file" [main 829c970] modified requirement file 3 files changed, 420 insertions(+), 451 deletion..

docker commit ContainerName ContainerName:Tag How to create image from container. It created 'commit_test:first' image. $ docker run -i -t --name commit_test ubuntu:14.04 //Create ubuntu container root@ac71ee960c10:/# echo test_first! >>first $ docker commit commit_test commit_test:first //Create 'commit_test:first'image sha256:e87f81e9b28ac369d9284d1b066219caed0ca22ce4539efb6825a9883257bdc4 $ d..

FP-growth Frequent Pattern Growth, is used as an analytical process that finds frequent patterns or associations from data sets. It greatly reduces the size of the itemset in the database by one simple principle which is if an itemset is frequent, then all of its subsets must also be frequent. It only scans the database twice and used a tree structure(FP-tree) to store all the information. The r..

mlxtend Machine Learning Extensions, a Python library of useful tools for the day-to-day data science tasks. - TransactionEncoder We can transform this dataset into an array format suitable for typical machine learning APIs. The NumPy array is boolean for the sake of memory efficiency when working with large datasets. fit : the TransactionEncoder learns the unique labels in the dataset transform..

Apriori - An algorithm for extracting frequent itemsets with applications in association rule learning. - The apriori algorithm has been designed to operate on databases containing transactions, such as purchases by customers of a store. - An itemset is considered as "frequent" if it meets a user-specified support threshold. For instance, if the support threshold is set to 0.5 (50%), a frequent ..