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Data Mining Lecture -- Decision Tree | Solved Example (Eng-Hindi)
 
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-~-~~-~~~-~~-~- Please watch: "PL vs FOL | Artificial Intelligence | (Eng-Hindi) | #3" https://www.youtube.com/watch?v=GS3HKR6CV8E -~-~~-~~~-~~-~-
Views: 208643 Well Academy
Decision Tree with Solved Example in English | DWM | ML | BDA
 
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Take the Full Course of Artificial Intelligence What we Provide 1) 28 Videos (Index is given down) 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in Artificial Intelligence Sample Notes : https://goo.gl/aZtqjh To buy the course click https://goo.gl/H5QdDU if you have any query related to buying the course feel free to email us : [email protected] Other free Courses Available : Python : https://goo.gl/2gftZ3 SQL : https://goo.gl/VXR5GX Arduino : https://goo.gl/fG5eqk Raspberry pie : https://goo.gl/1XMPxt Artificial Intelligence Index 1)Agent and Peas Description 2)Types of agent 3)Learning Agent 4)Breadth first search 5)Depth first search 6)Iterative depth first search 7)Hill climbing 8)Min max 9)Alpha beta pruning 10)A* sums 11)Genetic Algorithm 12)Genetic Algorithm MAXONE Example 13)Propsotional Logic 14)PL to CNF basics 15) First order logic solved Example 16)Resolution tree sum part 1 17)Resolution tree Sum part 2 18)Decision tree( ID3) 19)Expert system 20) WUMPUS World 21)Natural Language Processing 22) Bayesian belief Network toothache and Cavity sum 23) Supervised and Unsupervised Learning 24) Hill Climbing Algorithm 26) Heuristic Function (Block world + 8 puzzle ) 27) Partial Order Planing 28) GBFS Solved Example
Views: 286188 Last moment tuitions
Decision Tree Classification Algorithm – Solved Numerical Question 1 in Hindi
 
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Decision Tree Classification Algorithm – Solved Numerical Question 1 in Hindi Data Warehouse and Data Mining Lectures in Hindi
Decision Tree 1: how it works
 
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Full lecture: http://bit.ly/D-Tree A Decision Tree recursively splits training data into subsets based on the value of a single attribute. Each split corresponds to a node in the. Splitting stops when every subset is pure (all elements belong to a single class) -- this can always be achieved, unless there are duplicate training examples with different classes.
Views: 533220 Victor Lavrenko
Data Mining - Decision tree
 
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Decision tree represents decisions and decision Making. Root Node,Internal Node,Branch Node and leaf Node are the Parts of Decision tree Decision tree is also called Classification tree. Examples & Advantages for decision tree is explained. Data mining,text Mining,information Extraction,Machine Learning and Pattern Recognition are the fileds were decision tree is used. ID3,c4.5,CART,CHAID, MARS are some of the decision tree algorithms. when Decision tree is used for classification task, it is also called classification tree.
Decision Tree Induction (in Hindi)
 
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This Video is about Decision Tree Classification in Data Mining.
Views: 25049 Red Apple Tutorials
Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorithms | Edureka
 
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** Machine Learning with Python : https://www.edureka.co/machine-learning-certification-training ** This Edureka video on Decision Tree Algorithm in Python will take you through the fundamentals of decision tree machine learning algorithm concepts and its demo in Python. Below are the topics covered in this tutorial: 1. What is Classification? 2. Types of Classification 3. Classification Use Case 4. What is Decision Tree? 5. Decision Tree Terminology 6. Visualizing a Decision Tree 7 Writing a Decision Tree Classifier fro Scratch in Python using CART Algorithm Subscribe to our channel to get video updates. Hit the subscribe button above. Check out our Python Machine Learning Playlist: https://goo.gl/UxjTxm #decisiontree #decisiontreepython #machinelearningalgorithms - - - - - - - - - - - - - - - - - About the Course Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience. After completing this Machine Learning Certification Training using Python, you should be able to: Gain insight into the 'Roles' played by a Machine Learning Engineer Automate data analysis using python Describe Machine Learning Work with real-time data Learn tools and techniques for predictive modeling Discuss Machine Learning algorithms and their implementation Validate Machine Learning algorithms Explain Time Series and it’s related concepts Gain expertise to handle business in future, living the present - - - - - - - - - - - - - - - - - - - Why learn Machine Learning with Python? Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 76157 edureka!
Decision Tree Algorithm With Example | Decision Tree In Machine Learning | Data Science |Simplilearn
 
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This Decision Tree algorithm in Machine Learning tutorial video will help you understand all the basics of Decision Tree along with what is Machine Learning, problems in Machine Learning, what is Decision Tree, advantages and disadvantages of Decision Tree, how Decision Tree algorithm works with solved examples and at the end we will implement a Decision Tree use case/ demo in Python on loan payment prediction. This Decision Tree tutorial is ideal for both beginners as well as professionals who want to learn Machine Learning Algorithms. Below topics are covered in this Decision Tree Algorithm Tutorial: 1. What is Machine Learning? ( 02:25 ) 2. Types of Machine Learning? ( 03:27 ) 3. Problems in Machine Learning ( 04:43 ) 4. What is Decision Tree? ( 06:29 ) 5. What are the problems a Decision Tree Solves? ( 07:11 ) 6. Advantages of Decision Tree ( 07:54 ) 7. How does Decision Tree Work? ( 10:55 ) 8. Use Case - Loan Repayment Prediction ( 14:32 ) What is Machine Learning: Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Machine Learning Articles: https://www.simplilearn.com/what-is-artificial-intelligence-and-why-ai-certification-article?utm_campaign=Decision-Tree-Algorithm-With-Example-RmajweUFKvM&utm_medium=Tutorials&utm_source=youtube To gain in-depth knowledge of Machine Learning, check our Machine Learning certification training course: https://www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course?utm_campaign=Decision-Tree-Algorithm-With-Example-RmajweUFKvM&utm_medium=Tutorials&utm_source=youtube #MachineLearningAlgorithms #Datasciencecourse #DataScience #SimplilearnMachineLearning #MachineLearningCourse - - - - - - - - About Simplilearn Machine Learning course: A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning. - - - - - - - Why learn Machine Learning? Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period. - - - - - - What skills will you learn from this Machine Learning course? By the end of this Machine Learning course, you will be able to: 1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling. 2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project. 3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning. 4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more. 5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems - - - - - - - Who should take this Machine Learning Training Course? We recommend this Machine Learning training course for the following professionals in particular: 1. Developers aspiring to be a data scientist or Machine Learning engineer 2. Information architects who want to gain expertise in Machine Learning algorithms 3. Analytics professionals who want to work in Machine Learning or artificial intelligence 4. Graduates looking to build a career in data science and Machine Learning - - - - - - For more updates on courses and tips follow us on: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 50891 Simplilearn
Data Mining & Business Intelligence | Tutorial #27 | Decision Trees (Solved Problem)
 
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Order my books at 👉 http://www.tek97.com/ #RanjiRaj #DataMining #DecisionTrees Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj This video shows you how to solve a decision tree problem in data mining. Watch Now! يوضح لك هذا الفيديو كيفية حل مشكلة شجرة القرارات في استخراج البيانات. شاهد الآن ! Este vídeo mostra como resolver um problema da árvore de decisão na mineração de dados. Assista agora ! Это видео показывает, как решить проблему дерева решений в интеллектуальном анализе данных. Смотри ! Cette vidéo vous montre comment résoudre un problème d'arbre de décision dans l'exploration de données. Regarde maintenant ! Dieses Video zeigt Ihnen, wie Sie ein Entscheidungsbaumproblem im Data Mining lösen können. Schau jetzt ! Este video muestra cómo resolver un problema de árbol de decisión en la extracción de datos. Ver ahora ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 1579 Ranji Raj
entropyAndGain
 
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This video describes ID3, A seminal algorithm to build decision trees from example data. It is basic and its intention is to explain it for people who know little math, but can punch numbers on a calculator. This is based on Tom Mitchel's book
Views: 38369 Francisco Iacobelli
Data Mining - Decision Tree
 
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Use a view to make predictions about bike purchases.
Views: 11665 Mike
Decision Tree Important Points ll Machine Learning ll DMW ll Data Analytics ll Explained in Hindi
 
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Decision Tree Explained with Example https://youtu.be/RVuy1ezN_qA 📚📚📚📚📚📚📚📚 GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING 🎓🎓🎓🎓🎓🎓🎓🎓 SUBJECT :- Discrete Mathematics (DM) Theory Of Computation (TOC) Artificial Intelligence(AI) Database Management System(DBMS) Software Modeling and Designing(SMD) Software Engineering and Project Planning(SEPM) Data mining and Warehouse(DMW) Data analytics(DA) Mobile Communication(MC) Computer networks(CN) High performance Computing(HPC) Operating system System programming (SPOS) Web technology(WT) Internet of things(IOT) Design and analysis of algorithm(DAA) 💡💡💡💡💡💡💡💡 EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. 💡💡💡💡💡💡💡💡 THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING 📚📚📚📚📚📚📚📚
Views: 37956 5 Minutes Engineering
Decision Tree Classification in R
 
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This video covers how you can can use rpart library in R to build decision trees for classification. The video provides a brief overview of decision tree and the shows a demo of using rpart to create decision tree models, visualise it and predict using the decision tree model
Views: 80646 Melvin L
Decision Tree Algorithm & Analysis | Machine Learning Algorithm | Data Science Training | Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) This Edureka Decision Tree tutorial will help you understand all the basics of Decision tree. This decision tree tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts, learn decision tree analysis along with examples. Below are the topics covered in this tutorial: 1) Machine Learning Introduction 2) Classification 3) Types of classifiers 4) Decision tree 5) How does Decision tree work? 6) Demo in R Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #decisiontree #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "
Views: 66075 edureka!
Let’s Write a Decision Tree Classifier from Scratch - Machine Learning Recipes #8
 
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Hey everyone! Glad to be back! Decision Tree classifiers are intuitive, interpretable, and one of my favorite supervised learning algorithms. In this episode, I’ll walk you through writing a Decision Tree classifier from scratch, in pure Python. I’ll introduce concepts including Decision Tree Learning, Gini Impurity, and Information Gain. Then, we’ll code it all up. Understanding how to accomplish this was helpful to me when I studied Machine Learning for the first time, and I hope it will prove useful to you as well. You can find the code from this video here: https://goo.gl/UdZoNr https://goo.gl/ZpWYzt Books! Hands-On Machine Learning with Scikit-Learn and TensorFlow https://goo.gl/kM0anQ Follow Josh on Twitter: https://twitter.com/random_forests Check out more Machine Learning Recipes here: https://goo.gl/KewA03 Subscribe to the Google Developers channel: http://goo.gl/mQyv5L
Views: 229125 Google Developers
Decision Tree Learning using ID3 Algorithm | Artificial intelligence | Machine Learning
 
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#askfaizan | #syedfaizanahmad | #decisiontree PlayList : Artificial Intelligence : https://www.youtube.com/playlist?list=PLhwpdymnbXz4fEjqBoJbvLTIqfZJfXjbH Bayesian Network in Artificial Intelligence | Bayesian Belief Network | https://youtu.be/0U5xH4b7nPc Decision Tree Learning using ID3 Algorithm | Artificial intelligence https://youtu.be/pvTejBgiF3I Supervised Learning and Unsupervised Learning | Learning in Artificial Intelligence https://youtu.be/Wn2JgBfAsSM Genetic Algorithm | Artificial Intelligence Tutorial in Hindi Urdu https://youtu.be/frB2zIpOOBk Comparison of Search Algorithm https://youtu.be/QMz7jwXDvwg Resolution in Artificial Intelligence | Resolution Rules in AI https://youtu.be/oQmqJPLqHZA Inference rules in Predicate logic https://youtu.be/Y8KCh4VRRwM Predicate logic in AI | First order logic in Artificial Intelligence https://youtu.be/sFINpc5KA3E Wumpus World Proving | Propositional logic Example https://youtu.be/bDu9iNJ8h58 PROPOSITIONAL LOGIC | Artificial Intelligence https://youtu.be/oUR11UUIDvA Knowledge based Agents | Logical agents https://youtu.be/Y7CS-1BfA6o Alpha Beta Pruning | Problem #2 https://youtu.be/QL-g1FDls74 A Decision tree represents a function that takes as input a vector of attribute values and returns a “decision”—a single output value. The input and output values can be discrete or continuous. A decision tree reaches its decision by performing a sequence of tests. There are many specific decision-tree algorithms. Notable ones include: ID3 (Iterative Dichotomiser 3) C4.5 (successor of ID3) CART (Classification And Regression Tree) CHAID (Chi-squared Automatic Interaction Detector). Performs multi-level splits when computing classification trees. MARS: extends decision trees to handle numerical data better. ID3 is one of the most common decision tree algorithm Dichotomisation means dividing into two completely opposite things. Algorithm iteratively divides attributes into two groups which are the most dominant attribute and others to construct a tree. Then, it calculates the Entropy and Information Gains of each attribute. In this way, the most dominant attribute can be founded. After then, the most dominant one is put on the tree as decision node. Entropy and Gain scores would be calculated again among the other attributes. Procedure continues until reaching a decision for that branch. algorithm steps: Calculate the entropy of every attribute using the data set S Entropy(S) = ∑ – p(I) . log2p(I) Split the set S into subsets using the attribute for which the resulting entropy (after splitting) is minimum (or, equivalently, information gain is maximum) Gain(S, A) = Entropy(S) – ∑ [ p(S|A) . Entropy(S|A) ] Make a decision tree node containing that attribute Recurse on subsets using remaining attributes. for Complete Artificial Intelligence Videos click on the link : https://www.youtube.com/playlist?list=PLhwpdymnbXz4fEjqBoJbvLTIqfZJfXjbH Thank you for watching share with your friends Follow on : Facebook page : https://www.facebook.com/askfaizan1/ Instagram page : https://www.instagram.com/ask_faizan/ Twitter : https://twitter.com/ask_faizan/
Views: 45076 Ask Faizan
Data Mining with Weka (3.4: Decision trees)
 
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Data Mining with Weka: online course from the University of Waikato Class 3 - Lesson 4: Decision trees http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/1LRgAI https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 72908 WekaMOOC
Decision Tree In R | Decision Tree Algorithm | Data Science Tutorial | Machine Learning |Simplilearn
 
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This Decision Tree in R tutorial video will help you understand what is decision tree, what problems can be solved using decision trees, how does a decision tree work and you will also see a use case implementation in which we do survival prediction using R. Decision tree is one of the most popular Machine Learning algorithms in use today, this is a supervised learning algorithm that is used for classifying problems. It works well classifying for both categorical and continuous dependent variables. In this algorithm, we split the population into two or more homogeneous sets based on the most significant attributes/ independent variables. In simple words, a decision tree is a tree-shaped algorithm used to determine a course of action. Each branch of the tree represents a possible decision, occurrence or reaction. Now let us get started and understand how does Decision tree work. Below topics are explained in this Decision tree in R tutorial : 1. What is Decision tree? 2. What problems can be solved using Decision Trees? 3. How does a Decision Tree work? 4. Use case: Survival prediction in R Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 You can also go through the Slides here: https://goo.gl/WsM21R Watch more videos on Machine Learning: https://www.youtube.com/watch?v=7JhjINPwfYQ&list=PLEiEAq2VkUULYYgj13YHUWmRePqiu8Ddy #MachineLearningAlgorithms #Datasciencecourse #DataScience #SimplilearnMachineLearning #MachineLearningCourse About Simplilearn Machine Learning course: A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning. Why learn Machine Learning? Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period. What skills will you learn from this Machine Learning course? By the end of this Machine Learning course, you will be able to: 1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling. 2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project. 3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning. 4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more. 5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems We recommend this Machine Learning training course for the following professionals in particular: 1. Developers aspiring to be a data scientist or Machine Learning engineer 2. Information architects who want to gain expertise in Machine Learning algorithms 3. Analytics professionals who want to work in Machine Learning or artificial intelligence 4. Graduates looking to build a career in data science and Machine Learning Learn more at https://www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course?utm_campaign=Decision-Tree-in-R-HmEPCEXn-ZM&utm_medium=Tutorials&utm_source=youtube For more updates on courses and tips follow us on: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 6481 Simplilearn
Decision Tree Classification Algorithm – Solved Numerical Question 2 in Hindi
 
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Decision Tree Classification Algorithm – Solved Numerical Question 2 in Hindi Data Warehouse and Data Mining Lectures in Hindi
Data Mining | Decision Tree | Decision Tree Analysis | Decision Tree Example
 
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Data Mining | Decision Tree | Decision Tree Analysis | Decision Tree Example *********************************************** data mining, decision tree algorithm, decision tree learning algorithm, decision tree algorithm example, decision tree algorithm in data mining, decision tree algorithm in r, decision tree, Decision Tree Basic, decision tree algorithm, decision tree analysis, decision tree machine learning, decision tree learning, decision tree learning example, decision tree entropy, decision tree regression, decision making process, decision making, decision tree examples, decision tree maker, decision tree classifier, decision tree python, Please Subscribe My Channel
Views: 1912 Learning With Mahamud
Machine Learning with Python - Part 2: Decision Tree
 
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In this series, we'll explore machine learning with Python by building a classifier to determine whether or not we might like a song based on its attributes, which are provided by the Spotify API. We'll use an existing data set from Kaggle to explore and implement various classifiers. In Part 2, we'll create a Decision Tree classifier and visualize it using graphviz, pydotplus, scipy, and matplotlib! I'll speak briefly about the advantages and disadvantages of Decision Tree classifiers. If you enjoy my videos, support me on Patreon! https://www.patreon.com/wesdoyle Throughout this series, we'll: - Perform Exploratory Data Analysis (EDA) in a Jupyter Notebook using Pandas, Numpy, matplotlib, and other commonly-used libraries - Build a Decision Tree classifier using scikit-learn - Build a Random Forest classifier using scikit-learn - Build an Artificial Neural Network classifier using Keras Links: Link to the dataset on Kaggle: https://www.kaggle.com/geomack/spotifyclassification Intro track is adapted from "despondency" by Fog Lake, used with permission from the artist. Go check out his music, it's fantastic! - https://foglake.bandcamp.com/
Views: 28933 Wes Doyle
Decision Tree -Data mining in Visual studio 2013
 
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How to create Decision Tree in Visual studio 2013
Views: 338 Nex Console
Decision Tree Algorithm Explained With Example ll DMW ll ML Easiest Explanation Ever in Hindi
 
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Decision Tree Algorithm Part 2 https://youtu.be/ffZ0ShPi-wg 📚📚📚📚📚📚📚📚 GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING 🎓🎓🎓🎓🎓🎓🎓🎓 SUBJECT :- Artificial Intelligence(AI) Database Management System(DBMS) Software Modeling and Designing(SMD) Software Engineering and Project Planning(SEPM) Data mining and Warehouse(DMW) Data analytics(DA) Mobile Communication(MC) Computer networks(CN) High performance Computing(HPC) Operating system System programming (SPOS) Web technology(WT) Internet of things(IOT) Design and analysis of algorithm(DAA) 💡💡💡💡💡💡💡💡 EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. 💡💡💡💡💡💡💡💡 THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING 📚📚📚📚📚📚📚📚 Decision Tree Algorithm DMW Data Mining And Warehousing Information Gain Entropy formula Gain Formula Decision Tree Solved Example
Views: 47847 5 Minutes Engineering
decision tree example(ID3)
 
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Download this sum PDF from link below http://britsol.blogspot.in/2017/10/decision-tree-algorithm-pdf.html?m=1 book name: techmax publications datawarehousing and mining by arti deshpande n pallavi halarnkar
Views: 60042 fun 2 code
Predicting Target variable Values in Decision Tree Using Weka
 
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Hi Everyone, We usually create a data model but we restrict ourselves till the model creation but we actually don't predict the future values. This video is about how you can predict the target variable values in decision tree. I have used Weka for this implementation. The data set i have used is "Vote" dataset which comes along with Weka. I create 2 data sets - one was Training data set without last 30 rows, and Test data set with last 30 rows but no values for target variable. You can create test data set with "?" implanted for target values in test set.
Views: 5095 Nitin Paighowal
Decision Tree with R | Complete Example
 
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Also called Classification and Regression Trees (CART) or just trees. R file: https://goo.gl/Kx4EsU Data file: https://goo.gl/gAQTx4 Includes, - Illustrates the process using cardiotocographic data - Decision tree and interpretation with party package - Decision tree and interpretation with rpart package - Plot with rpart.plot - Prediction for validation dataset based on model build using training dataset - Calculation of misclassification error Decision trees are an important tool for developing classification or predictive analytics models related to analyzing big data or data science. R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 58999 Bharatendra Rai
DECISION TREE INDUCTION
 
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Views: 1367 Caraline Raj
Decision tree algorithm | classifier in data mining
 
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In this video, I explained Decision tree algorithm | classifier of data mining with the example and how to construct Decision tree from data.
Data Mining Decision Tree example
 
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Data Mining Decision Tree example شرح داتامايننك نيورال نيتورك
Views: 32172 Sudets1
Decision Tree C4.5 Implementation
 
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Data Mining Project -- C4.5 Decision Tree Implementation CMU Team Supernova
Views: 14680 Charlotte Lin
Data Mining with Weka (3.5: Pruning decision trees)
 
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Data Mining with Weka: online course from the University of Waikato Class 3 - Lesson 5: Pruning decision trees http://weka.waikato.ac.nz/ Slides (PDF): https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 39539 WekaMOOC
MS SQL Server Data mining- decision tree
 
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A quick example on how to do data mining using decision tree algorithm within MS SQL Server . We analyze patterns in data that is heavily skewed for specific cases so that we can validate the model.
Views: 5674 Jayanth Kurup
Data Mining Lecture Bangla -- Decision Tree।Solved Example Part 1
 
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A decision tree is a structure that includes a root node, branches, and leaf nodes. Each internal node denotes a test on an attribute, each branch denotes the outcome of a test, and each leaf node holds a class label. The topmost node in the tree is the root node. Email : [email protected]
Views: 1879 Asaduzzaman Kanok
ID3 Algorithm ll Decision Tree Algorithm ll Explained with Examples in Hindi
 
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Views: 23475 5 Minutes Engineering
Decision Tree (CART) - Machine Learning Fun and Easy
 
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Decision Tree (CART) - Machine Learning Fun and Easy ►FREE YOLO GIFT - http://augmentedstartups.info/yolofreegiftsp ►KERAS Course - https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML Decision tree is a type of supervised learning algorithm (having a pre-defined target variable) that is mostly used in classification problems. A tree has many analogies in real life, and turns out that it has influenced a wide area of machine learning, covering both classification and regression (CART). So a decision tree is a flow-chart-like structure, where each internal node denotes a test on an attribute, each branch represents the outcome of a test, and each leaf (or terminal) node holds a class label. The topmost node in a tree is the root node. ------------------------------------------------------------ Support us on Patreon ►AugmentedStartups.info/Patreon Chat to us on Discord ►AugmentedStartups.info/discord Interact with us on Facebook ►AugmentedStartups.info/Facebook Check my latest work on Instagram ►AugmentedStartups.info/instagram Learn Advanced Tutorials on Udemy ►AugmentedStartups.info/udemy ------------------------------------------------------------ To learn more on Artificial Intelligence, Augmented Reality IoT, Deep Learning FPGAs, Arduinos, PCB Design and Image Processing then check out http://augmentedstartups.info/home Please Like and Subscribe for more videos :)
Views: 156465 Augmented Startups
5. Building Decision Tree Models using RapidMiner Studio
 
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This video describes (1) how to build a decision tree model, (2) how to interpret a decision tree, and (3) how to evaluate the model using a classification matrix.
Views: 19045 Pallab Sanyal
Technical Course: Decision Trees: Decision Tree Analysis
 
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Decision Tree Tutorial and Introduction by Jigsaw Academy. This is part one of the Decision Tree tutorial from our Foundation Analytics course (http://www.jigsawacademy.com/online-analytics-training). In this example, we look at how decision trees can be used by credit card companies to market themselves to a target audience of potentially profitable customers. Jigsaw Academy is an award winning premier online analytics training institute that aims to meet the growing demand for talent in the field of analytics by providing industry-relevant training to develop business-ready professionals.Jigsaw Academy has been acknowledged by blue chip companies for quality training. Follow us on: https://www.facebook.com/jigsawacademy https://twitter.com/jigsawacademy http://jigsawacademy.com/
Views: 86744 Jigsaw Academy
Data Mining Lecture -- Rule - Based Classification (Eng-Hindi)
 
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-~-~~-~~~-~~-~- Please watch: "PL vs FOL | Artificial Intelligence | (Eng-Hindi) | #3" https://www.youtube.com/watch?v=GS3HKR6CV8E -~-~~-~~~-~~-~-
Views: 42788 Well Academy
C4.5 algorithm and Multivariate Decision Trees
 
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The aim of this presentation is to show a brief description about the C4.5 algorithm, used to create Univariate Decision Trees. We also talk about Multivariate Decision Trees, their process to classify instances using more than one attribute per node in the tree. We try to discuss how they work, and how to implement the algorithms that build such trees, including examples of Univariate and Multivariate results.
Views: 54449 Thales Sehn Körting
Lecture - 35 Rule Induction and Decision Trees - II
 
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Lecture Series on Artificial Intelligence by Prof.Sudeshna Sarkar and Prof.Anupam Basu, Department of Computer Science and Engineering,I.I.T, Kharagpur . For more details on NPTEL visit http://nptel.iitm.ac.in.
Views: 15184 nptelhrd
Creating Decision Tree Using ID3 and J48 in Weka 3.6.3 Tool for Data Mining
 
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This video is made as a part of Digital Assignment number 2 of Data Mining Course (CSE3019) in Vellore Institute of Technology, Vellore. Name: Deep Baldha Registration No.: 16BCE0421
Views: 2444 Deep Baldha
Gini Index | Decision Tree - Part 1 (Hindi - English)
 
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This video is the simplest hindi english explanation of gini index in decision tree induction for attribute selection measure.
Views: 38053 Red Apple Tutorials
j48 Decision tree using Weka
 
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Tutorial : How to use Weka tool to display decision tree. Steps : 1)Enter given table in excel 2)save file as weather, in csv file format (select file format from dropdown) 3)open weka 4)click explore 5)open the csv file from weka 6)select classify tab 6)choose j48 7)use traning set 8)start 9)right click on result and visualize. By Darshit Vora Change to high quality.
Views: 58306 Kushal Bhabra
link spam detection using decision trees in orange (data mining)
 
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in this video i will be discussing about link spam detection using decision tree classifier
Views: 553 Anshuman singh
Top 5 Data Science Algorithms - Decision Tree, Random Forest, Linear Regression, K-Means | Edureka
 
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This Data Science Tutorial delves into the top 5 data science algorithms that expert data scientists use. It's a great big data tutorial for beginners and will help you understand decision trees, data mining, association rule mining etc.
Views: 52184 edureka!
Lecture - 26 Learning : Decision Trees
 
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Lecture Series on Artificial Intelligence by Prof. P. Dasgupta, Department of Computer Science & Engineering, IIT Kharagpur. For more Courses visit http://nptel.iitm.ac.in
Views: 116555 nptelhrd