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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: 31942 Red Apple Tutorials
GINI Index With a Simple Example - Gain in Gini Index (Decision Tree Induction Algorithm)
 
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Gini Index in Data Mining: Today, we will learn to calculate gain in Gini Index when splitting on A and B Attribute. Find out which attribute would the decision tree induction algorithm choose. Question: Consider the following data set for a binary problems. Table: Given in Video --Calculate the gain in the Gini index when splitting on A and B. Which Attribute would the decision tree induction algorithm choose? --Calculate the information gain when splitting on A and B. Which attribute would the decision tree induction algorithm choose ? Hope you Guys liked this video and found this helpful if yes so please Hit on SUBSCRIBE button. Check out our website : http://www.technofun.tk/ Don''t Forget To Check Out These Videos[You Gotta Watch These At-least Once] Most Recent Upload: https://goo.gl/7AaULr Most Popular Upload: https://goo.gl/5216JU I ***************Likes & Subscribe **************** ***************HELP US TO GROW*************** ***************SUPPORT NEEDED**************** Follow us on Facebook:- https://www/facebook.com/Techitechno Follow us on Instagram:- https://www.instagram.com/technofuns TAKE CARE YOU TUBERS & STAY BLESSED :)
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 #decisiontree #Gini #machinelearning
Views: 27616 Bhavesh Bhatt
gini Index example explanation  - Part 2 in Hindi
 
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explanation of induction of decision tree using gini index in hindi
Views: 14574 Red Apple Tutorials
The Gini Index
 
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A Measure of Inequality
Views: 6425 Bryant Mathews
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
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: 192914 Well Academy
Gini index in data mining
 
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In this video, I explained that how to find gini index of an attribute in data mining.
Views: 4560 DataMining Tutorials
Gain Chart | Logistic Regression | Model Monitoring |Model Validation
 
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In this video you will learn what is Gain chart and how is it constructed. You will also learn how to use gain chart in logistic regression for model monitoring Contact [email protected]
Views: 7432 Analytics University
Gini Index from Decision Trees and Lorenz Curve
 
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Recorded with https://screencast-o-matic.com
Views: 136 Purvaja Balaji
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: 249972 Last moment tuitions
Gini Index Examples
 
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2 quick calculations of a Gini Index
Views: 365 Amy Frankel
Gain ratio in data mining
 
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In this video, I explained that how to find gain ratio of an attribute in data mining.
Views: 4757 DataMining Tutorials
12_Classification3 GINI INDEX
 
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کەمپینى بە کوردى کردنى زانست لە زانکۆى گەشە پێدانى مرۆیی
Views: 12716 shanga abdulla
Understanding the Gini Coefficient
 
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This video explains the concept of Gini Coefficient using simple illustrations.
V-03-B Gini Index
 
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Views: 309 Saif Rahman
4 Gini Index
 
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Views: 1205 John Sieben
datamining Gini index
 
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Views: 5443 Lana luqman
Data Impurity and Entropy
 
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This video is part of an online course, Intro to Machine Learning. Check out the course here: https://www.udacity.com/course/ud120. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 19546 Udacity
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: 183576 Victor Lavrenko
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: 218492 Google Developers
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. .
Decision Tree - Splitting Criterion & Entropy Calculation | Part-3
 
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The challenge in the decision tree implementation is to identify which attributes do we need to consider as the root node and each level. Attributes selection is important here. We have different attributes selection measures to identify an attribute which can be considered as the root note at each level. Learn the importance of a good splitting criterion and attribute selection measure – entropy. Entropy calculation is explained in detail in the video. Entropy characterizes the purity/impurity of a variable. It’s an indicator of how messy your data is. For the detailed video tutorials, code files, data-sets and other material, please visit our site https://statinfer.com/ This video is part of the e-learning course - Machine Learning with Python (https://statinfer.com/course/machine-learning-with-python-2/)
Views: 1332 Statinfer Analytics
Decision Treee | Entropy | Information Gain || Simply Explained
 
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Mohamed Mnete: Here I try my best to answer the question of what a decision tree is, how it is created, and how it is used. I explain this in the context of entropy and information gain. Please LIKE, SHARE, SUBSCRIBE AND comment any questions you may have. Live, Laugh, Study and Love!
Views: 231 Muddy Jeff
Gini Index
 
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Example calculating the Gini index. This is an application of the area between curves
Views: 282 Christopher Vaughen
information Gain | Decision Tree (in Hindi)
 
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This video is a hindi explanation about attribute selection measure and describe about information gain in data mining
Views: 5825 Red Apple Tutorials
Data mining in urdu   part 19
 
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classification - decision tree induction. Information gain, gini index, entropy
Views: 48 Pak Project
soran hasan data mining gini index
 
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classification
Views: 284 Soran Hasan
12_Gini index part3/4
 
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کەمپینی بە کوردی کردنی زانست لە زانکۆی گەشەپێدانی مرۆیی Data Mining Classification Gini Index
Views: 1713 salim hasan
The Gini Coefficient
 
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This video introduces the Gini coefficient, which is a way to summarize income inequality using a single number. For more information and a complete listing of videos and online articles by topic or textbook chapter, see http://www.economistsdoitwithmodels.com/economics-classroom/ For t-shirts and other EDIWM items, see http://www.economistsdoitwithmodels.com/merch/ By Jodi Beggs - Economists Do It With Models http://www.economistsdoitwithmodels.com Facebook: http://www.facebook.com/economistsdoitwithmodels Twitter: http://www.twitter.com/jodiecongirl Tumblr: http://economistsdoitwithmodels.tumblr.com
Views: 107418 jodiecongirl
Decision Tree in R
 
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Here I will describe about what is decision tree,how to implement decision tree model in R,how to plot roc curve in decision tree in R,implement decision tree using rpart,calculate auc in R,decision tree using rpart #machinelearning #decisiontree #R
What is GINI COEFFICIENT? What does GINI COEFFICIENT mean? GINI COEFFICIENT meaning & explanation
 
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✪✪✪✪✪ WORK FROM HOME! Looking for WORKERS for simple Internet data entry JOBS. $15-20 per hour. SIGN UP here - http://jobs.theaudiopedia.com ✪✪✪✪✪ ✪✪✪✪✪ The Audiopedia Android application, INSTALL NOW - https://play.google.com/store/apps/details?id=com.wTheAudiopedia_8069473 ✪✪✪✪✪ What is GINI COEFFICIENT? What does GINI COEFFICIENT mean? GINI COEFFICIENT meaning - GINI COEFFICIENT definition -GINI COEFFICIENT explanation. The Gini coefficient (also known as the Gini index or Gini ratio) is a measure of statistical dispersion intended to represent the income distribution of a nation's residents, and is the most commonly used measure of inequality. It was developed by the Italian statistician and sociologist Corrado Gini and published in his 1912 paper Variability and Mutability (Italian: Variabilita e mutabilita). The Gini coefficient measures the inequality among values of a frequency distribution (for example, levels of income). A Gini coefficient of zero expresses perfect equality, where all values are the same (for example, where everyone has the same income). A Gini coefficient of 1 (or 100%) expresses maximal inequality among values (e.g., for a large number of people, where only one person has all the income or consumption, and all others have none, the Gini coefficient will be very nearly one). However, a value greater than one may occur if some persons represent negative contribution to the total (for example, having negative income or wealth). For larger groups, values close to or above 1 are very unlikely in practice. Given the normalization of both the cumulative population and the cumulative share of income used to calculate the Gini coefficient, the measure is not overly sensitive to the specifics of the income distribution, but rather only on how incomes vary relative to the other members of a population. The exception to this is in the redistribution of wealth resulting in a minimum income for all people. When the population is sorted, if their income distribution were to approximate a well known function, then some representative values could be calculated. The Gini coefficient was proposed by Gini as a measure of inequality of income or wealth. For OECD countries, in the late 20th century, considering the effect of taxes and transfer payments, the income Gini coefficient ranged between 0.24 and 0.49, with Slovenia the lowest and Chile the highest. African countries had the highest pre-tax Gini coefficients in 2008–2009, with South Africa the world's highest, variously estimated to be 0.63 to 0.7, although this figure drops to 0.52 after social assistance is taken into account, and drops again to 0.47 after taxation. The global income Gini coefficient in 2005 has been estimated to be between 0.61 and 0.68 by various sources. There are some issues in interpreting a Gini coefficient. The same value may result from many different distribution curves. The demographic structure should be taken into account. Countries with an aging population, or with a baby boom, experience an increasing pre-tax Gini coefficient even if real income distribution for working adults remains constant. Scholars have devised over a dozen variants of the Gini coefficient.
Views: 7988 The Audiopedia
Decision Tree 4: Information Gain
 
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Full lecture: http://bit.ly/D-Tree After a split, we end up with several subsets, which will have different values of entropy (purity). Information Gain (aka mutual information) is an average of these entropies, weighted by the size of each subset.
Views: 159768 Victor Lavrenko
Decision Tree Algorithm Explained With Example ll DMW 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: 27803 5 Minutes Engineering
Gini index part 1
 
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Views: 918 Shwan Barzan
Gini Index Calculation from a Lorenz Function
 
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This video shows how to calculate the Gini Index that corresponds to a given Lorenz function, using either the fundamental theorem of calculus or the function integration (fnInt) command on a TI83 graphing calculator. The meaning of the Gini Index is also explained.
Views: 53259 Hands On Math
Gini Index
 
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An Easy Overview Of "Gini Index"
Views: 1979 Christopher Hunt
Decision Trees Continuous Attributes - Georgia Tech - Machine Learning
 
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Watch on Udacity: https://www.udacity.com/course/viewer#!/c-ud262/l-313488098/m-641939067 Check out the full Advanced Operating Systems course for free at: https://www.udacity.com/course/ud262 Georgia Tech online Master's program: https://www.udacity.com/georgia-tech
Views: 16350 Udacity
Evaluating Classifiers: Kolmogorov-Smirnov Chart (K-S Chart)
 
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My web page: www.imperial.ac.uk/people/n.sadawi
Views: 11637 Noureddin Sadawi
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: 56640 Bharatendra Rai
Shannon Entropy and Information Gain
 
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Blog post: https://medium.com/p/5810d35d54b4/
Views: 50711 Luis Serrano
jaccard coefficient similarity in hindi urdu in data mining
 
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http://www.t4tutorials.com/jaccard-coefficient-similarity-measure-for-asymmetric-binary-variables/ data mining full lectures in hindi, data mining full lectures in urdu, similarity by jaccard coefficient, Jaccard simmilarity, Thank you very much to https://t4tutorials.com Like Our Page: https://www.facebook.com/t4tutorialsOfficial/ For Business Queries: +923028700085 Email: [email protected]
Views: 3255 University Of Shamil
Data GINI from WorldBank
 
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This video is created by recording from http://data.worldbank.org/indicator/SI.POV.GINI/countries/1W-ID-US-PH?page=1&display=map This is just a way to present it simpler
Views: 96 Satria Priambada

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