Search results “Decision tree examples in data mining ppt”
Decision Tree Induction (in Hindi)
This Video is about Decision Tree Classification in Data Mining.
Views: 18414 Red Apple Tutorials
Creative Decision Tree Diagram in PowerPoint
Creative Decision Tree Diagram in PowerPoint Follow this step by step screencast tutorial for a simple decision tree diagram to use in your next presentation. Key Links: ********** 25 Creative Ideas MINI Training http://www.presentation-process.com/25-creative-presentation-ideas-mini-training.html Comprehensive All In One Bundle - PowerPoint Templates: http://www.presentation-process.com/comprehensive-all-in-one-powerpoint-bundle.html Ramgopal's PowerPoint Mastery Training Program: http://www.presentation-process.com/ramgopals-powerpoint-mastery-program.html
Views: 4272 Presentation Process
Decision Tree Tutorial in 7 minutes with Decision Tree Analysis & Decision Tree Example (Basic)
Clicked here http://www.MBAbullshit.com/ and OMG wow! I'm SHOCKED how easy.. No wonder others goin crazy sharing this??? Share it with your other friends too! Fun MBAbullshit.com is filled with easy quick video tutorial reviews on topics for MBA, BBA, and business college students on lots of topics from Finance or Financial Management, Quantitative Analysis, Managerial Economics, Strategic Management, Accounting, and many others. Cut through the bullshit to understand MBA!(Coming soon!) http://www.youtube.com/watch?v=a5yWr1hr6QY
Views: 535704 MBAbullshitDotCom
Decision Tree 1: how it works
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: 483488 Victor Lavrenko
Decision Tree Analysis IN HINDI With  Solved Practical by JOLLY Coaching
This video is about DECISION TREE ANALYSIS which will help you to understand the basic concept of decision tree analysis. In this video i have solved one practical question which will help you to get the process of solving any numerical question and example. After watching you will also get to know that how to construct the decision tree. I hope this will help you. Thanks JOLLY Coaching how to solve decision tree problem, Decision tree analysis, How to solve decision tree analysis, Practical solved questios on decision tree analysis. decision threoy decision tree analysis
Views: 100930 JOLLY Coaching
How to Make Decision Tree Diagram in PowerPoint
Creative Decision Tree Diagram in PowerPoint. Follow this step by step screencast tutorial for a simple decision tree diagram and then download the template from here: https://www.infodiagram.com/diagrams/decision-tree-powerpoint-template-flowchart.html?cp=camp5 SUBSCRIBE to the Channel: ⭐ https://www.youtube.com/channel/UCDS32TnwA3dJWh9ZvWyhhYQ?sub_confirmation=1 🔥 Click on 'Show More' for details (...) #TreeDiagram #Powerpoint #LinkInTheDescription More creative ideas on our blog: https://blog.infodiagram.com/2018/12/present-decision-making-process-diagram-powerpoint.html?cp=camp5 Share this video: https://youtu.be/A4QmBRJpHCI How to make an awesome presentation in a minute? Use more visuals & illustrations instead of text. See examples of PPT graphics and editable slide diagrams. Thanks to them you can create a professional and easy to understand slides. WATCH OUR CHANNEL PLAYLISTS 👉🏻 Creative Powerpoint: https://www.youtube.com/watch?v=tFH2tEnXnJA&list=PLXqGbN2k3HJ57o5HaXLi82NCf1ZoHLkXK 👉🏻 Concept Videos: https://www.youtube.com/watch?v=m3_1S0K2Ec0&list=PLXqGbN2k3HJ4arPaFNvIhLzopEbMzoLzS 👉🏻 Narrated: https://www.youtube.com/watch?v=bWCjpNtVDGQ&list=PLXqGbN2k3HJ6jN6_ywjNFnfBDWA7tVYvJ ✔️ You can find us on: 🔺 Facebook: https://www.facebook.com/infoDiagram 🔺 Twitter: https://twitter.com/infodiagram 🔺 Website: https://www.infodiagram.com/?cp=camp5 🔺 Blog: https://blog.infodiagram.com?cp=camp5 🔺 Slideshare: http://www.slideshare.net/infoDiagram Comments are welcomed!
Data Mining - Decision tree
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.
DecisionTree ID3
the meaning of ID3_of Decision Tree Classification and example of it .
Views: 165 Ali Othman
Data Mining Classification - Basic Concepts
Classification in Data Mining with classification algorithms. Explanation on classification algorithm the decision tree technique with Example.
Data Mining - Clustering
What is clustering Partitioning a data into subclasses. Grouping similar objects. Partitioning the data based on similarity. Eg:Library. Clustering Types Partitioning Method Hierarchical Method Agglomerative Method Divisive Method Density Based Method Model based Method Constraint based Method These are clustering Methods or types. Clustering Algorithms,Clustering Applications and Examples are also Explained.
شجرة القرارات - Decision Trees
Download slides from here: https://drive.google.com/file/d/0BwkBn0oFDraSX2hIRTVVWXlnQlE/view?usp=sharing
Views: 59653 Ibrahim Almosallam
Data Mining Lecture -- Bayesian Classification | Naive Bayes Classifier | Solved Example (Eng-Hindi)
In the bayesian classification The final ans doesn't matter in the calculation Because there is no need of value for the decision you have to simply identify which one is greater and therefore you can find the final result. -~-~~-~~~-~~-~- Please watch: "PL vs FOL | Artificial Intelligence | (Eng-Hindi) | #3" https://www.youtube.com/watch?v=GS3HKR6CV8E -~-~~-~~~-~~-~-
Views: 153350 Well Academy
Decision Tree Algorithm With Example | Decision Tree In Machine Learning | Data Science |Simplilearn
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: 28241 Simplilearn
What is Random Forest Algorithm? A graphical tutorial on how Random Forest algorithm works?
It Explains Random Forest Method in a very simple and pictorial way --------------------------------- Read in great detail along with Excel output, computation and R code ---------------------------------- https://www.udemy.com/decision-tree-theory-application-and-modeling-using-r/?couponCode=Ad_Try_01
Views: 111792 Gopal Malakar
Data Mining Classification and Prediction ( in Hindi)
A tutorial about classification and prediction in Data Mining .
Views: 28303 Red Apple Tutorials
data mining fp growth | data mining fp growth algorithm | data mining fp tree example | fp growth
In this video FP growth algorithm is explained in easy way in data mining Thank you for watching share with your friends Follow on : Facebook : https://www.facebook.com/wellacademy/ Instagram : https://instagram.com/well_academy Twitter : https://twitter.com/well_academy data mining algorithms in hindi, data mining in hindi, data mining lecture, data mining tools, data mining tutorial, data mining fp tree example, fp growth tree data mining, fp tree algorithm in data mining, fp tree algorithm in data mining example, fp tree in data mining, data mining fp growth, data mining fp growth algorithm, data mining fp tree example, data mining fp tree example, fp growth tree data mining, fp tree algorithm in data mining, fp tree algorithm in data mining example, fp tree in data mining, data mining, fp growth algorithm, fp growth algorithm example, fp growth algorithm in data mining, fp growth algorithm in data mining example, fp growth algorithm in data mining examples ppt, fp growth algorithm in data mining in hindi, fp growth algorithm in r, fp growth english, fp growth example, fp growth example in data mining, fp growth frequent itemset, fp growth in data mining, fp growth step by step, fp growth tree
Views: 123590 Well Academy
Prediction Analysis of Heart Patients using Naive Bayes and Random Forest Algorithms
Introduction Heart Diseases remain the biggest cause of deaths for the last two epochs. Recently computer technology develops software to assistance doctors in making decision of heart disease in the early stage. Diagnosing the heart disease mainly depends on clinical and obsessive data. Prediction system of Heart disease can assist medical experts for predicting heart disease current status based on the clinical data of various patients. In this project, the Heart disease prediction using classification algorithm Naive Bayes, and Random Forest is discussed. Naive Bayes Algorithm The Naive Bayes classification algorithm is a probabilistic classifier. It is based on probability models that incorporate strong independence assumptions. Naive Bayes is a simple technique for constructing classifiers models that assign class labels to problem instances. It assume that the value of a particular feature is independent of the value of any other feature, given the class variable. For example, a fruit may be considered to be an apple if it is red, round, and about 10 cm in diameter. A naive Bayes classifier considers each of these features to contribute independently to the probability that this fruit is an apple, regardless of any possible correlations between the color, roundness, and diameter features. Random Forest Technique In this technique, a set of decision trees are grown and each tree votes for the most popular class, then the votes of different trees are integrated and a class is predicted for each sample. This approach is designed to increase the accuracy of the decision tree, more trees are produced to vote for class prediction. This approach is an ensemble classifier composed of some decision trees and the final result is the mean of individual trees results. Follow Us: Facebook : https://www.facebook.com/E2MatrixTrainingAndResearchInstitute/ Twitter: https://twitter.com/e2matrix_lab/ LinkedIn: https://www.linkedin.com/in/e2matrix-thesis-jalandhar/ Instagram: https://www.instagram.com/e2matrixresearch/
Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorithms | Edureka
** 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: 40030 edureka!
Decision Trees - Example 1
In this video, you will learn how to solve a decision making problem using decision trees
Views: 37474 maxus knowledge
Decision Tree Analysis with Example and Expected Value - Easy & Fun Calculation
Decision Tree Analysis is used to determine the expected value of a project in business. This video takes a step-by-step look at how to figure out the best optimized decision to use. SUBSCRIBE: https://goo.gl/atM3GS MORE VIDEOS: https://goo.gl/u1GBXN WEBSITE: https://goo.gl/LSfThB TWITTER: https://goo.gl/3Hlifb LINKEDIN: https://goo.gl/B42VPU GET OUR EBOOK: https://goo.gl/ogTxwJ
Views: 13694 Nick Harrison
How To Make Decision Tree In Excel
DTREE is customised Excel file which helps to automate decision tree calculation and drawing in Excel.
Views: 2433 Santosh Singh
Decision Tree Building based on Impurity for KDD or Machine Learning
In this video, I create a decision tree using Gini Impurity to determine the splitting attributes. I originally created this video (and the others in my series) to be used with a specific KDD class which is taught at my home university. I first encountered this algorithm in class there. If you would like to look into this topic in more detail, or read a bit about some similar algorithms, I am including the link to one of the presentations that I used as a reference. coitweb.uncc.edu/~ras/KBS-Class/1-Decision-Trees.ppt Thank you for watching!
Views: 45052 Laurel Powell
How Decision Trees Work
Decision trees are powerful and surprisingly straightforward. Here's how they are grown. Code: https://github.com/brohrer/brohrer.github.io/blob/master/code/decision_tree.py Slides: https://docs.google.com/presentation/d/1fyGhGxdGcwt_eg-xjlMKiVxstLhw42XfGz3wftSzRjc/edit?usp=sharing PERMISSIONS: Original video was published with the Creative Commons Attribution license (reuse allowed). CREDITS: Original video source: https://www.youtube.com/watch?v=9w16p4QmkAI
Views: 7189 Coding Tech
Lecture 73 — Decision Trees | Mining of Massive Datasets | Stanford University
. 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. .
Final Year Projects  | Decision Trees for Mining Data Streams Based on the McDiarmid's Bound
Including Packages ======================= * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 356 Clickmyproject
Classification ppt
Data mining term project
Views: 72 parul singh
Lecture - 26 Learning : Decision Trees
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: 115110 nptelhrd
Introduction to data mining and architecture  in hindi
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: 190579 Last moment tuitions
Decision Trees in Excel: Choice Nodes
Micro-lesson on building decision tree models in MS Excel
Views: 1100 Dan Ryan
Decision Tree for Classification Problems | data Science
In this video you will learn about building a decision tree models for classification problem. Decision tree is a supervised learning algorithm. It can be used to classify data into categories. It is similar to other classification algorithms such as Logistic Regression, Multi nominal Logistic regression, Random forest, Support vector Machine , deep learning. Contact : [email protected] ANalytics Study Pack : http://analyticuniversity.com/ Analytics University on Twitter : https://twitter.com/AnalyticsUniver Analytics University on Facebook : https://www.facebook.com/AnalyticsUniversity Logistic Regression in R: https://goo.gl/S7DkRy Logistic Regression in SAS: https://goo.gl/S7DkRy Logistic Regression Theory: https://goo.gl/PbGv1h Time Series Theory : https://goo.gl/54vaDk Time ARIMA Model in R : https://goo.gl/UcPNWx Survival Model : https://goo.gl/nz5kgu Data Science Career : https://goo.gl/Ca9z6r Machine Learning : https://goo.gl/giqqmx Data Science Case Study : https://goo.gl/KzY5Iu Big Data & Hadoop & Spark: https://goo.gl/ZTmHOA
Views: 4206 Analytics University
Creating Simple Decision Tree with Add-in
Using the Excel add-in to create a very simple decision tree
Views: 15245 profMattDean
Random Forest - Fun and Easy Machine Learning
Random Forest - Fun and Easy Machine Learning ►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 Hey Guys, and welcome to another Fun and Easy Machine Learning Algorithm on Random Forests. Random forest algorithm is a one of the most popular and most powerful supervised Machine Learning algorithm in Machine Learning that is capable of performing both regression and classification tasks. As the name suggest, this algorithm creates the forest with a number of decision trees. In general, the more trees in the forest the more robust the prediction. In the same way in the random forest classifier, the higher the number of trees in the forest gives the high accuracy results. To model multiple decision trees to create the forest you are not going to use the same method of constructing the decision with information gain or gini index approach, amongst other algorithms. If you are not aware of the concepts of decision tree classifier, Please check out my lecture here on Decision Tree CART for Machine learning. You will need to know how the decision tree classifier works before you can learn the working nature of the random forest algorithm. ------------------------------------------------------------ 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: 180378 Augmented Startups
Prediction and Classification with Decision Tree
This vlog introduces you to decision tree in R and how categorical data can be classified and predicted by this algorithm.
Views: 1828 Keshav Singh
Naive Bayes Theorem | Introduction to Naive Bayes Theorem | Machine Learning Classification
Naive Bayes is a machine learning algorithm for classification problems. It is based on Bayes’ probability theorem. It is primarily used for text classification which involves high dimensional training data sets. A few examples are spam filtration, sentimental analysis, and classifying news articles. It is not only known for its simplicity, but also for its effectiveness. It is fast to build models and make predictions with Naive Bayes algorithm. Naive Bayes is the first algorithm that should be considered for solving text classification problem. Hence, you should learn this algorithm thoroughly. This video will talk about below: 1. Machine Learning Classification 2. Naive Bayes Theorem About us: HackerEarth is building the largest hub of programmers to help them practice and improve their programming skills. At HackerEarth, programmers: 1. Solve problems on Algorithms, DS, ML etc(https://goo.gl/6G4NjT). 2. Participate in coding contests(https://goo.gl/plOmbn) 3. Participate in hackathons(https://goo.gl/btD3D2) Subscribe Our Channel For More Updates : https://goo.gl/suzeTB For More Updates, Please follow us on: Facebook : https://goo.gl/40iEqB Twitter : https://goo.gl/LcTAsM LinkedIn : https://goo.gl/iQCgJh Blog : https://goo.gl/9yOzvG
Views: 80396 HackerEarth
Decision Tree using Silver Decisions
In this example we will use SilverDecisions for creating a Decision Tree and evaluating it. Link: http://silverdecisions.pl
Views: 369 Khalid Khan
Decision Trees - Business A-level Revision Video - Study Rocket
Explaining business decision trees. Access our exam based, Business Studies course delivered in an environment that stops procrastination - https://studyrocket.co.uk/courses/business-a-level/ Study without procrastination. #business #alevel #ocr #aqa #studyrocket
Views: 133 Study Rocket
Decision Tree
Decision Tree for PowerPoint presentations. Get this graph at http://www.poweredtemplate.com/powerpoint-diagrams-charts/ppt-tree-diagrams/00040/0/index.html Download creative, pre-made, and complete editable diagrams, shapes, icons and charts at http://www.PoweredTemplate.com
Views: 298 PoweredTemplate.com
Decision Stream: Cultivating Deep Decision Trees
IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2017): "Decision Stream: Cultivating Deep Decision Trees". PowerPoint presentation: https://www.slideshare.net/DmitryIgnatovPhD/decision-stream-cultivating-deep-decision-trees
Views: 26350 Dmitry Yu. Ignatov
Data Science & Machine Learning - C5.0 Decision Tree Exercise - DIY- 27 -of-50
Data Science & Machine Learning - C5.0 Decision Tree Exercise - DIY- 27 -of-50 Do it yourself Tutorial by Bharati DW Consultancy cell: +1-562-646-6746 (Cell & Whatsapp) email: [email protected] website: http://bharaticonsultancy.in/ Google Drive- https://drive.google.com/open?id=0ByQlW_DfZdxHeVBtTXllR0ZNcEU C5.0 Decision Tree - Classification C50_model{anglebrace}- C5.0(train_Predictors, train_Target) C50_predict{anglebrace}- predict(C50_model, test_data) Get the data from Balance Scale Data Set. http://archive.ics.uci.edu/ml/datasets/Balance+Scale Citation Policy: If you publish material based on databases obtained from this repository, then, in your acknowledgements, please note the assistance you received by using this repository. This will help others to obtain the same data sets and replicate your experiments. We suggest the following pseudo-APA reference format for referring to this repository: Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science. Here is a BiBTeX citation as well: @misc{Lichman:2013 , author = "M. Lichman", year = "2013", title = "{UCI} Machine Learning Repository", url = "http://archive.ics.uci.edu/ml", institution = "University of California, Irvine, School of Information and Computer Sciences" } Data Science & Machine Learning - Getting Started - DIY- 1 -of-50 Data Science & Machine Learning - R Data Structures - DIY- 2 -of-50 Data Science & Machine Learning - R Data Structures - Factors - DIY- 3 -of-50 Data Science & Machine Learning - R Data Structures - List & Matrices - DIY- 4 -of-50 Data Science & Machine Learning - R Data Structures - Data Frames - DIY- 5 -of-50 Data Science & Machine Learning - Frequently used R commands - DIY- 6 -of-50 Data Science & Machine Learning - Frequently used R commands contd - DIY- 7 -of-50 Data Science & Machine Learning - Installing RStudio- DIY- 8 -of-50 Data Science & Machine Learning - R Data Visualization Basics - DIY- 9 -of-50 Data Science & Machine Learning - Linear Regression Model - DIY- 10(a) -of-50 Data Science & Machine Learning - Linear Regression Model - DIY- 10(b) -of-50 Data Science & Machine Learning - Multiple Linear Regression Model - DIY- 11 -of-50 Data Science & Machine Learning - Evaluate Model Performance - DIY- 12 -of-50 Data Science & Machine Learning - RMSE & R-Squared - DIY- 13 -of-50 Data Science & Machine Learning - Numeric Predictions using Regression Trees - DIY- 14 -of-50 Data Science & Machine Learning - Regression Decision Trees contd - DIY- 15 -of-50 Data Science & Machine Learning - Method Types in Regression Trees - DIY- 16 -of-50 Data Science & Machine Learning - Real Time Project 1 - DIY- 17 -of-50 Data Science & Machine Learning - KNN Classification - DIY- 21 -of-50 Data Science & Machine Learning - KNN Classification Hands on - DIY- 22 -of-50 Data Science & Machine Learning - KNN Classification HandsOn Contd - DIY- 23 -of-50 Data Science & Machine Learning - KNN Classification Exercise - DIY- 24 -of-50 Data Science & Machine Learning - C5.0 Decision Tree Intro - DIY- 25 -of-50 Data Science & Machine Learning - C5.0 Decision Tree Use Case - DIY- 26 -of-50 Data Science & Machine Learning - C5.0 Decision Tree Exercise - DIY- 27 -of-50 Machine learning, data science, R programming, Deep Learning, Regression, Neural Network, R Data Structures, Data Frame, RMSE & R-Squared, Regression Trees, Decision Trees, Real-time scenario, KNN, C5.0 Decision Tree,
Data Mining  Association Rule - Basic Concepts
short introduction on Association Rule with definition & Example, are explained. Association rules are if/then statements used to find relationship between unrelated data in information repository or relational database. Parts of Association rule is explained with 2 measurements support and confidence. types of association rule such as single dimensional Association Rule,Multi dimensional Association rules and Hybrid Association rules are explained with Examples. Names of Association rule algorithm and fields where association rule is used is also mentioned.
Data Mining Tutorial: Understanding CART Splitters, Competitors, And Surrogates
http://www.salford-systems.com/support This tutorial will help you improve your understanding of CART data mining models within the Salford Predictive Modeler.
Views: 889 Salford Systems
C4.5 algorithm and Multivariate Decision Trees
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.
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Decision Tree
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Decision Tree Creation
Part 2 of Decision Tree Analysis: Using Visio to create a Decision Tree and applying the technique to a sample problem.
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Pruning in Generalized Sequence Pattern (GSP) Algorithm
This is additional material for Advanced Data Mining Class of WILP Students. It addresses pruning in GSP.
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How Artificial Neural Network (ANN) Algorithm Work | Data Mining | Introduction to Neural Network
#ArtificialNeuralNetwork | Beginners guide to how artificial neural network model works. Learn how neural network approaches the problem, why and how the process works in ANN, various ways errors can be used in creating machine learning models and ways to optimise the learning process. - Watch our new free Python for Data Science Beginners tutorial: https://greatlearningforlife.com/python - Visit https://greatlearningforlife.com our learning portal for 100s of hours of similar free high-quality tutorial videos on Python, R, Machine Learning, AI and other similar topics Know More about Great Lakes Analytics Programs: PG Program in Business Analytics (PGP-BABI): http://bit.ly/2f4ptdi PG Program in Big Data Analytics (PGP-BDA): http://bit.ly/2eT1Hgo Business Analytics Certificate Program: http://bit.ly/2wX42PD #ANN #MachineLearning #DataMining #NeuralNetwork About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/
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