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Decision Tree with Solved Example in English | DWM | ML | BDA
 
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Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://goo.gl/to1yMH or Fill the form we will contact you https://goo.gl/forms/2SO5NAhqFnjOiWvi2 if you have any query email us at [email protected] or [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 147374 Last moment tuitions
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: 142973 Well Academy
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: 454845 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 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
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: 80038 Jigsaw Academy
Data Mining Decision Tree example
 
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Data Mining Decision Tree example شرح داتامايننك نيورال نيتورك
Views: 28664 Sudets1
Decision Tree (CART) - Machine Learning Fun and Easy
 
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Decision Tree (CART) - Machine Learning Fun and Easy 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. To learn more on Augmented Reality, IoT, Machine Learning FPGAs, Arduinos, PCB Design and Image Processing then Check out http://www.arduinostartups.com/ Please like and Subscribe for more videos :) -------------------------------------------------- Support us on Patreon http://bit.ly/PatreonArduinoStartups --------------------------------------------------
Views: 93259 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: 11279 Pallab Sanyal
Data Mining - Decision Tree
 
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Use a view to make predictions about bike purchases.
Views: 10938 Mike
Lecture 73 — Decision Trees | Mining of Massive Datasets | Stanford University
 
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. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "FAIR USE" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. .
شجرة القرارات - Decision Trees
 
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Download slides from here: https://drive.google.com/file/d/0BwkBn0oFDraSX2hIRTVVWXlnQlE/view?usp=sharing
Views: 53883 Ibrahim Almosallam
Prediction and Classification with Decision Tree
 
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This vlog introduces you to decision tree in R and how categorical data can be classified and predicted by this algorithm.
Views: 1609 Keshav Singh
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: 1011 Asaduzzaman Kanok
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 Please write back to us at [email protected] or call us at +918880862004 or 18002759730 for more information. 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: 52373 edureka!
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] Call us at US: +18336900808 (Toll Free) or India: +918861301699 Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 23828 edureka!
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: 54998 Kushal Bhabra
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
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: 67797 Melvin L
Decision Tree Induction (in Hindi)
 
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This Video is about Decision Tree Classification in Data Mining.
Views: 13141 Red Apple Tutorials
CART-Classification and Regression Trees
 
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Gini Index in CART Entropy Pruning CART Cost Complexity Cost Complexity Pruning Classification and Regression Trees Pruning
Views: 9618 Sunil Bhatia
Lecture 75 — Information Gain | Mining of Massive Datasets | Stanford University
 
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. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "FAIR USE" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. .
SSAS - Data Mining - Decision Trees, Clustering, Neural networks
 
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SSAS - Data Mining - Decision Trees, Clustering, Neural networks
Views: 991 M R Dhandhukia
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: 65487 WekaMOOC
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: 26767 Francisco Iacobelli
(ML 2.1) Classification trees (CART)
 
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Basic intro to decision trees for classification using the CART approach. A playlist of these Machine Learning videos is available here: http://www.youtube.com/my_playlists?p=D0F06AA0D2E8FFBA
Views: 100064 mathematicalmonk
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: 18636 Simplilearn
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: 54737 fun 2 code
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: 4663 Jayanth Kurup
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: 35479 WekaMOOC
How Decision Trees Work 1/2 .. an Introduction + What is Entropy
 
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My web page: www.imperial.ac.uk/people/n.sadawi
Views: 49798 Noureddin Sadawi
Decision Tree Learning using ID3 Algorithm | Artificial intelligence | Machine Learning
 
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#askfaizan | #syedfaizanahmad PlayList : Artificial Intelligence : https://www.youtube.com/playlist?list=PLhwpdymnbXz4fEjqBoJbvLTIqfZJfXjbH 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: 8204 Ask Faizan
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: 16744 Red Apple Tutorials
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: 113955 nptelhrd
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: 45611 Bharatendra Rai
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: 1038 Learning With Mahamud
Data Mining Metode Klasifikasi dengan Algortma Decision Tree
 
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Proses Memining Data dengan Menggunakan Salah satu metode pada data mining yaitu metode clasification dengan algoritma Decision Tree, adapun data yang kami olah yaitu data kelulusan dari salah satu program studi tahun 2015
Views: 4882 Wahyu Saputra
Gini index based Decision Tree
 
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How does a Decision Tree Work? A Decision Tree recursively splits training data into subsets based on the value of a single attribute. Splitting stops when every subset is pure (all elements belong to a single class) and OMG wow! I'm SHOCKED how easy it was .. No wonder others going crazy sharing this??? Share it with your other friends too! Code for visualising a decision tree - https://github.com/bhattbhavesh91/visualize_decision_tree Please Subscribe! That is the thing you could do that would make me happiest. You can find me on: GitHub - https://github.com/bhattbhavesh91 Medium - https://medium.com/@bhattbhavesh91
Views: 12934 Bhavesh Bhatt
Decision Tree 5: overfitting and pruning
 
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Full lecture: http://bit.ly/D-Tree A decision tree can always classify the training data perfectly (unless there are duplicate examples with different class labels). In the process of doing this, the tree might over-fit to the peculiarities of the training data, and will not do well on the future data (test set). We avoid overfitting by pruning the decision tree.
Views: 95155 Victor Lavrenko
Belajar Data Mining - Algoritma Decision Tree C4.5
 
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Algoritma C4.5 adalah salah satu metode pada Decision Tree / Pohon Keputusan yang banyak dimanfaatkan untuk melakukan prediksi terhadap suatu kasus. Selamat Belajar, Jangan lupa untuk subscribe, like dan share Terima kasih atas support kalian!
Views: 7118 Wong AiTi
StatQuest: Decision Trees
 
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This StatQuest focuses on the machine learning topic "Decision Trees". Decision trees are a simple way to convert a table of data that you have sitting around your desk into a means to predict and classify new data as it comes. For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider a StatQuest t-shirt or sweatshirt... https://teespring.com/stores/statquest ...or buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/
Data Mining Lecture Bangla -- Decision Tree।Solved Example Part 2
 
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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: 592 Asaduzzaman Kanok
Decision Tree 3: which attribute to split on?
 
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Full lecture: http://bit.ly/D-Tree Which attribute do we select at each step of the ID3 algorithm? The attribute that results in the most pure subsets. We can measure purity of a subset as the entropy (degree of uncertainty) about the class within the subset.
Views: 162512 Victor Lavrenko
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.
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: 234 Anshuman Singh