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SLIQ: A Fast Scalable Classifier for Data Mining Manish Mehta, Rakesh Agrawal, Jorma Rissanen 1996. Presentation by: Vladan Radosavljevic Outline Introduction ...

Decision Trees SLIQ fast scalable classifier Group 12-Vaibhav Chopda-Tarun Bahadur Paper By - Manish Mehta, Rakesh Agarwal and Jorma Rissanen Source http ...

Replace this repeated sorting with one-time sort. Use new a data structure call class-list ... are projections on (rid, attribute). SLIQ - Sort Numeric, Group ...

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Chapter 26: Data Mining (Some s courtesy of Rich Caruana, Cornell University) Definition Data mining is the exploration and analysis of large quantities of data ...

Decision Tree Classification Tomi Yiu CS 632 Advanced Database Systems April 5, 2001 Papers Manish Mehta, Rakesh Agrawal, Jorma Rissanen: SLIQ: A Fast Scalable ...

Title: 1 Last modified by: Document presentation format: (4:3) Other titles: Arial Calibri Monotype Sorts Times New Roman ...

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Title: PowerPoint Presentation Author: SLCHAN Last modified by: Africa Pig Created Date: 10/11/2002 4:18:07 AM Document presentation format: On-screen Show

Scaling Decision Tree Induction Outline Why do we need scaling? Cover state of the art methods Details on my research (which is one of the state of the art methods ...

Dept. of Computer Science 15-415 - Database Applications C. Faloutsos Data Warehousing / Data Mining General Overview Relational model SQL; db design Indexing; Q ...

There could be more than one tree that fits the same data! Splitting ... Larger and Purer Partitions are sought for. Yes. B? No. Node N1. Node N2. Gini(N1) ...

Title: Steven F. Ashby Center for Applied Scientific Computing Month DD, 1997 Author: Computations Last modified by: Luis Otavio Created Date: 3/18/1998 1:44:31 PM

Title: Odkrywanie regu asocjacyjnych Author: Nguyen Hung Son Last modified by: son Created Date: 10/8/2002 4:07:23 PM Document presentation format

Classification: Basic Concepts, Decision Trees, and Model Evaluation Lecture Notes for Chapter 4 Introduction to Data Mining by Tan, Steinbach, Kumar

Spontaneity, Entropy, Free Energy, and Why All Things Happen The Universe Becomes Less Predictable ZUMDAHL S CHAPTER 16

Classification and Prediction

Title: Steven F. Ashby Center for Applied Scientific Computing Month DD, 1997 Author: Computations Last modified by: James Jeffry Howbert Created Date

Classification: Basic Concepts, Decision Trees, and Model Evaluation Lecture Notes for Chapter 4 Introduction to Data Mining by Tan, Steinbach, Kumar

Classification: Basic Concepts, Decision Trees, and Model Evaluation COSC 4368

Find a model for class attribute as a function of the values of other ... Larger and Purer Partitions are sought for. B? Yes. No. Node N1. Node N2. Gini(N1) ...

Classification with Decision Trees Instructor: Qiang Yang Hong Kong University of Science and Technology Qyang@cs.ust.hk Thanks: Eibe Frank and Jiawei Han

Find a model for class attribute as a function of the values of other attributes. ... Categorizing news stories as finance, weather, entertainment, sports, etc ...

Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 1 ... Categorizing news stories as finance, weather, entertainment, sports, etc ...

Data Mining Classification: Basic Concepts, Decision Trees, and Model Evaluation Lecture Notes for Chapter 3 Examples of Classification Task Predicting tumor cells as ...

... (Pi); Proc dure de Construction (2) Processus r cursif L'arbre commence un n ud repr sentant toutes les donn es Si les objets sont de la m me classe, ...

Classification Classification vs. Prediction Classification: predicts categorical class labels classifies data (constructs a model) based on the training set and the ...

CS490D: Introduction to Data Mining Prof. Chris Clifton February 9, 2004 Classification Classification and Prediction What is classification? What is prediction?

Classification: Basic Concepts, Decision Trees, and Model Evaluation Lecture Notes for Chapter 4 Introduction to Data Mining by Tan, Steinbach, Kumar

Knowledge discovery & data mining: Classification UCLA CS240A Winter 2002 Notes from a tutorial presented @ EDBT2000 By Fosca Giannotti and Dino Pedreschi

Decision Tree. Problem Identification. Inference Class. Performance. Sparse Data ... It was proven that a decision tree with scale-up and parallel capability is very ...

SPRINT: A Scalable Parallel Classifier for Data Mining. IBM Almaden ... This paper present a decision-tree-based classification algorithm, called SPRINT ...

Trim the nodes of the decision tree in a bottom-up fashion. If generalization error improves after trimming, replace sub-tree by a leaf node. ...

Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 1 ... records that belong the same class yt, then t is a leaf node labeled as yt ...

Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 1 ... Larger and Purer Partitions are sought for. B? Yes. No. Node N1. Node N2. Gini(N1) ...

Requirements for an algorithm to be useful in a wide range of real-world applications: ... Dealing sensibly with missing values: a bit trickier ...

Data Mining, Data Warehousing and Knowledge Discovery Basic Algorithms and Concepts Srinath Srinivasa IIIT Bangalore sri@iiitb.ac.in Some MDBMS Operations Roll-up Add ...

Classification A Two-Step Process. Model construction: describing a set of predetermined classes ... Supervised learning (classification) ...

Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 1 ... Entropy = 0 log 0 1 log 1 = 0 0 = 0. P(C1) = 1/6 P(C2) = 5/6 ...

Title: Mining and Summarizing Customer Reviews Author: Preferred Customer Last modified by: factuser Created Date: 6/21/2004 3:23:40 AM Document presentation format

Tan,Steinbach, Kumar Introduction to Data Mining 4/18/2004 1 ... Categorizing news stories as finance, weather, entertainment, sports, etc ...

Data Mining, Data Warehousing and Knowledge Discovery ... which contain j as a sequence Sequence data: transaction logs, DNA sequences, patient ailment history, ...

Discretization to form an ordinal categorical attribute ... Attributes are categorical (if continuous-valued, they are discretized in advance) ...

1 Mflop/s 1 Megaflop/s 106 Flop/sec. 1 Gflop/s 1 Gigaflop/s 109 Flop/sec ... E.g., HPF, TreadMarks, sw for NoW (JavaParty, Manta, Jackal) 35 ...

Introduction k-NN Arbres de d cision R seaux baysiens R seaux de neurones Conclusion 1. Apprentissage supervis D couverte de r gles ou formules (patterns) pour ...

This material is modified and reproduced based on books and materials of P-N, ... Larger and Purer Partitions are sought for. B? Yes. No. Node N1. Node N2. Gini(N1) ...

Title: 1. Explosion de l'informatique d cisionnelle Author: GARDARIN Last modified by: GARDARIN Created Date: 5/28/1995 4:28:04 PM Document presentation format

Requirements for an algorithm to be useful in a wide range ... still a main-memory algorithm. Best known algorithms: ID3. C4.5. C5. 47. Efforts on Scalability ...

... Entropy (Refund=Yes) = 0 ... p is split into k partitions ni is the number of records in partition i Adjusts Information Gain by the entropy ... Decision Tree ...

Indexing Time Series using GEMINI' (GEneric Multimedia INdexIng) ... of (often large) observational data sets to find unsuspected relationships and ...

Classification by Support Vector Machines (SVM) Instance Based Methods. Prediction ... apply a statistical test (e.g., chi-square) to estimate whether expanding or ...

... analysis to externally known results, e.g., to externally given class labels. ... the extent to which cluster labels match externally supplied class labels. ...

Classification and Prediction - The Course Chapter Objectives Learn basic techniques for data classification and prediction. Realize the difference between the ...

Text mining, Web mining and Weblog analysis. Spatial, multimedia, scientific data analysis ... customization: home page Weblog user profiles. 9/3/09. Data ...

Avoid Overfitting in Classification The generated tree may overfit the training data Too many branches, some may reflect anomalies due to noise or outliers

Select splitting Criteria( Information gain, Gain ratio, Gini Index, Chi Square test) ... R., C4.5: Programs for Machine Learning, Morgan Kaufmann, San Mateo, ...