This video is the simplest hindi english explanation of gini index in decision tree induction for attribute selection measure.

Views: 25010
Red Apple Tutorials

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 :)

Views: 1869
ᴛᴇᴄʜɴᴏғᴜɴ

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: 20909
Bhavesh Bhatt

explanation of induction of decision tree using gini index in hindi

Views: 11280
Red Apple Tutorials

Views: 15499
amanj aladin

-~-~~-~~~-~~-~-
Please watch: "PL vs FOL | Artificial Intelligence | (Eng-Hindi) | #3"
https://www.youtube.com/watch?v=GS3HKR6CV8E
-~-~~-~~~-~~-~-

Views: 174543
Well Academy

Views: 858
Rawaz hassan

Views: 20214
Liam Malloy

Views: 3810
Paul Turner

Views: 1189
John Sieben

Machine Learning Bootcamp: http://bit.ly/machine-learning-deep-learning

Views: 11884
Balazs Holczer

In this video, I explained that how to find gini index of an attribute in data mining.

Views: 4194
DataMining Tutorials

In this video, I explained that how to find gain ratio of an attribute in data mining.

Views: 3799
DataMining Tutorials

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: 209628
Last moment tuitions

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: 174663
Victor Lavrenko

کەمپینى بە کوردى کردنى زانست لە زانکۆى گەشە پێدانى مرۆیی

Views: 12634
shanga abdulla

.
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.
.

Views: 9004
Artificial Intelligence - All in One

Recorded with https://screencast-o-matic.com

Views: 71
Purvaja Balaji

Views: 5362
Lana luqman

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: 51928
Hands On Math

Example calculating the Gini index. This is an application of the area between curves

Views: 255
Christopher Vaughen

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: 18535
Udacity

This video explains the concept of Gini Coefficient using simple illustrations.

Views: 18513
Singapore Department of Statistics

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: 152186
Victor Lavrenko

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: 194183
Google Developers

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: 14892
Udacity

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: 855
Statinfer Analytics

This video is a hindi explanation about attribute selection measure and describe about information gain in data mining

Views: 4441
Red Apple Tutorials

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: 45159
Laurel Powell

Views: 886
Shwan Barzan

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: 495286
Victor Lavrenko

The Gini coefficient is a measure of inequality of a distribution. It is defined as a ratio with values between 0 and 1: the numerator is the area between the Lorenz curve of the distribution and the uniform distribution line; the denominator is the area under the uniform distribution line. It was developed by the Italian statistician Corrado Gini and published in his 1912 paper "Variabilità e mutabilità" ("Variability and Mutability"). The Gini index is the Gini coefficient expressed as a percentage, and is equal to the Gini coefficient multiplied by 100. (The Gini coefficient is equal to half of the relative mean difference.)

Views: 3385
SanGeotics

Blog post: https://medium.com/p/5810d35d54b4/

Views: 44326
Luis Serrano

Chapter 8, week9
Data Mining - IT446

Views: 1315
Bayanbrui

My web page:
www.imperial.ac.uk/people/n.sadawi

Views: 11052
Noureddin Sadawi

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: 6711
Analytics University

CART, Classification and Regression Trees is a family of Supervised Machine Learning Algorithms.
Follow this link for an entire Intro course on Machine Learning using R, did I mention it's FREE:
https://www.youtube.com/playlist?list=PLjPbBibKHH18I0mDb_H4uP3egypHIsvMn
Also, be sure to check out my channel for over 400 tutorials on Excel, R, Statistics, Machine Learning, basic Math, and more.

Views: 11481
Jalayer Academy

کەمپینی بە کوردی کردنی زانست لە زانکۆی گەشەپێدانی مرۆیی
Data Mining Classification Gini Index

Views: 1490
salim hasan

کەمپینی بە کوردی کردنی زانست لە زانکۆی گەشەپێدانی مرۆیی
Data Mining - Classification - Gini Index

Views: 4169
salim hasan

Busi Calc Applications of Area Between Curves - Gini Index

Views: 2116
melathrop