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IBApriori Algorithm
هي تصنف من خوارزميات التنقيب في البيانات واكثر استخدام الها في
Market Basket analysis
مقالة عن الخوارزمية بقناة التلكرام الرابط بالبايو
@ibrahimihssan1
#Apriori Algorithm
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AIThe Apriori algorithm is an unsupervised machine learning algorithm used for association rule learning. It is a data mining technique used to identify frequent sets of items and association rules within large datasets, essentially finding patterns where certain items tend to appear together.
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@ai_education_academy
486
SAApriori and FP-growth Algorithm Explained!!
Youtube link- https://youtu.be/gwKh_OOg_rk
@sangeetha_vinothanand
972
PYKeep importance of features without loosing value😳👇
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Apriori algorithm can be used to identify frequent itemsets and association rules in a dataset. Using a sample dataset of transactions, the algorithm efficiently uncovers patterns and relationships among items, aiding in market basket analysis and decision-making processes.😉💻🐍
#apriori_algorithm #apriori #decision_making #machinelearning #unsupervisedlearning #marketbasketanalysis #marketbasket #datasets #data #relationship #rules
@pyprogrammings
17.4K
SLNothing reveals taste more than the ordinary.
Start with the detail you hold twice a day.
#Apriori #QuiteProper
@slim_by_apriori
470
CO🔍✨ What’s Association Rule Mining?
It’s like finding hidden shopping secrets 🛒 → figuring out which products are often bought together!
📌 Famous Examples:
👉 At Walmart, customers who buy diapers 🍼 often also pick up beer 🍺.
👉 At a grocery store, people buying bread & butter 🍞🧈 are also likely to buy jam 🍓.
👉 In online shopping, someone buying a phone 📱 often adds a cover & earphones 🎧 to their cart.
This is called Market Basket Analysis → helping stores arrange items smartly & cross-sell 🚀.
⚡ But how do we find these patterns?
That’s where the Apriori Algorithm comes in!
It works step by step:
1️⃣ Count frequent item combinations (Support).
2️⃣ Check how often one item leads to another (Confidence).
3️⃣ Measure the strength of the rule (Lift).
✨ Example Rule:
“If a customer buys diapers 🍼, then they also buy beer 🍺 with 70% confidence.”
So next time you see related items placed together, remember → it’s not luck, it’s Apriori magic + Data Science 🔮
#AI #MachineLearning #DataScience #RetailStrategy #Apriori #AssociationRuleMining #Walmart #MarketBasketAnalysis
@cosmicminds.in
92.9K
JOEncrypted Search Method for Cloud Computing Data Under Attack Based on TF-IDF and Apriori Algorithm
@journalclub.io
177.6K
RENov 16, 2025: This is actually happening January 1st. #healthcare #medicare #ai #aigovernance #medicalcare #seniors #disabledcommunity #trumpadministration #politics #news #breakingnews #healthcrisis #patients #doctors #medicaldenial #priorauthorization #cms #wiseprogram #policy #america #fyp #trending #viralnews #mustwatch #justice
@real.talk.us
635
COTop 10 machine learning algorithms Part B :
Logistic regression :
Logistic regression is a statistical model that in its basic form uses a logistic function to model a binary dependent variable, although many more complex extensions exist. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (a form of binary regression).
Naive bayes :
naive Bayes classifiers are a family of simple "probabilistic classifiers" based on applying Bayes' theorem with strong independence assumptions between the features. They are among the simplest Bayesian network models, but coupled with kernel density estimation, they can achieve higher accuracy levels
Support vector machines :
A support vector machine (SVM) is a supervised machine learning model that uses classification algorithms for two-group classification problems. After giving an SVM model sets of labeled training data for each category, they're able to categorize new text.
Apriori algorithm :
Apriori is an algorithm for frequent item set mining and association rule learning over relational databases. It proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as those item sets appear sufficiently often in the database.
K-means clustering :
k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster.
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@code.it.29
9.8K
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@apriori.spa.resort_
3.5K
BEКоли сказала, що з завтрашнього дня на дієті… а сьогодні вже в APRIORI Sushi
Замовляйте за телефоном: 097 801 3023
🏠 Самовивіз: м. Бобринець, вул. Базарна, 155
💻 Або на сайті (посилання в шапці профілю).
@bey_food_
4.8K
NFRaata Maar 😂😂#mids
@nfaklines.official
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