PPT-Information Gain, Decision Trees and Boosting
Author : solidbyte | Published Date : 2020-06-23
10701 ML recitation 9 Feb 2006 by Jure Entropy and Information Grain Entropy amp Bits You are watching a set of independent random sample of X X has 4 possible
Presentation Embed Code
Download Presentation
Download Presentation The PPT/PDF document "Information Gain, Decision Trees and Boo..." is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.
Information Gain, Decision Trees and Boosting: Transcript
10701 ML recitation 9 Feb 2006 by Jure Entropy and Information Grain Entropy amp Bits You are watching a set of independent random sample of X X has 4 possible values PXA14 PXB14 PXC14 PXD14. Lecture . 10. Decision Trees. G53MLE . Machine Learning. Dr . Guoping. Qiu. 1. Trees. Node. Root. Leaf. Branch. Path. Depth. 2. Decision Trees. A hierarchical data structure that represents data by implementing a divide and conquer strategy . Chapter 9. Topics. Two-Stage Op-Amps. Gain-Boosting. Input Rage Limitation. Slew Rate. Power Supply Rejection. Noise. Simple Implementation of a Two-Stage Op-Amp. Stage 1. Two-Stage Op-Amp Employing . Image . Denoising. Algorithms. The research leading to these results has received funding from the European Research Council under European Union's Seventh Framework . Program, . ERC Grant agreement no. . Decision Trees. Gavin Brown. www.cs.man.ac.uk/~gbrown. Recap: threshold classifiers. height. weight. Q. Where is a good threshold?. 10 20 30 40 50 60. 1. 0. Also known as “decision stump”. From Decision . David . Mease. & . Abraham . Wyner. What is the Statistical View? . The idea presented in . J. . Friedman, T. Hastie, and R. . Tibshirani. . Additive logistic regression: A statistical view of boosting. Annals of Statistics, 28:337–374, . Tandy Warnow. The University of Texas at Austin. Orangutan. Gorilla. Chimpanzee. Human. From the Tree of the Life Website,. University of Arizona. Phylogeny. (evolutionary tree). Applications. . of Phylogeny Estimation . Admin. Final project. Ensemble learning. Basic idea: . if one classifier works well, why not use multiple classifiers!. Ensemble learning. Basic idea: . if one classifier works well, why not use multiple classifiers!. Object-based classifiers. Others. DECISION TREES. Non-parametric approach. Data mining tool used in many applications, not just RS. Classifies data by building rules based on image values. Rules form trees that are multi-branched with nodes and “leaves” or endpoints. Chong Ho (Alex) Yu. Problems of bias and variance. The bias is . the . error which results from missing a target. . For . example, if an estimated mean is 3, but the actual population value is 3.5, then the bias value is 0.5. . Florina. . Balcan. 03/18/2015. Perceptron, Margins, Kernels. Recap from last time: Boosting. Works by creating . a series . of challenge datasets . s.t.. . even modest performance on these can . be . Decision trees MARIO REGIN What is a decision tree? General purpose prediction and classification mechanism Emerged at the same time as the nascent fields of artificial intelligence and statistical computation . by Holly Nguyen, Hongyu Pan, Lei Shi, Muhammad Tahir. Showcasing work by . Themis P. Exarchos, Alexandros T. Tzallas, DinaBaga, Dimitra Chaloglou, Dimitrios I. Fotiadis, Sofia Tsouli, Maria Diako. u. How is normal Decision Tree different from Random Forest?. A Decision Tree is a supervised learning strategy in machine learning. It may be used with both classification and regression algorithms. . As the name says, it resembles a tree with nodes. The branches are determined by the number of criteria. It separates data into these branches until a threshold unit is reached. . Want to keep your testosterone levels healthy? Eating these 5 best testosterone boosting foods that are high in nutrients & vitamins.
Download Document
Here is the link to download the presentation.
"Information Gain, Decision Trees and Boosting"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.
Related Documents