Lecture notes for econometrics

... better, customized services for an edge (e.g in Customer Relationship Management) © Tan,Steinbach, Kumar Introduction to Data Mining Why Mine Data? Scientific Viewpoint Data collected and stored at ... the data is never analyzed at all 4,000,000 3,500,000 The Data Gap 3,000,000 2,500,000 2,000,000 1, 500,000 Total new disk (TB) since 19 95 1, 000,000 Number of analysts 500...

Ngày tải lên: 15/03/2014, 09:20

... p2 p3 p4 p1 p3 p4 p2 0 y 1 p1 p1 p2 p3 p4 x 2. 828 3.1 62 5.099 p2 2. 828 1.414 3.1 62 p3 3.1 62 1.414 p4 5.099 3.1 62 Distance Matrix © Tan,Steinbach, Kumar Introduction to Data Mining 50 Minkowski ... Tan,Steinbach, Kumar Introduction to Data Mining 42 Mapping Data to a New Space Fourier transform Wavelet transform Two Sine Waves © Tan,Steinbach, Kumar Two Sine Wa...

Ngày tải lên: 15/03/2014, 09:20

... object Introduction to Data Mining separate face becomes a Star Plots for Iris Data Setosa Versicolour Virginica © Tan,Steinbach, Kumar Introduction to Data Mining 29 Chernoff Faces for Iris Data ... Tan,Steinbach, Kumar Introduction to Data Mining 35 OLAP Operations: Data Cube The key operation of a OLAP is the formation of a data cube A data cube is a...

Ngày tải lên: 15/03/2014, 09:20

... same data! 10 © Tan,Steinbach, Kumar Introduction to Data Mining Decision Tree Classification Task Decision Tree © Tan,Steinbach, Kumar Introduction to Data Mining Apply Model to Test Data Test Data ... P(C2) = 4/ 6 Error = – max (2/6, 4/ 6) = – 4/ 6 = 1/3 Introduction to Data Mining 43 Comparison among Splitting Criteria For a 2-class problem: © Tan...

Ngày tải lên: 15/03/2014, 09:20

... (3) until stopping criterion is met © Tan,Steinbach, Kumar Introduction to Data Mining 14 Example of Sequential Covering (ii) Step © Tan,Steinbach, Kumar Introduction to Data Mining 15 Example ... Tan,Steinbach, Kumar Introduction to Data Mining 27 Indirect Methods © Tan,Steinbach, Kumar Introduction to Data Mining 28 Indirect Method: C4.5rules Extract rules f...

Ngày tải lên: 15/03/2014, 09:20

... 159 3 56 357 68 9 Introduction to Data Mining 367 368 22 Subset Operation Using Hash Tree Hash Function transaction 1+ 23 56 2+ 3 56 12+ 3 56 1,4,7 3+ 56 3 ,6, 9 2,5,8 13+ 56 234 567 15+ 145 1 36 345 ... 159 Introduction to Data Mining 3 56 357 68 9 367 368 23 Subset Operation Using Hash Tree Hash Function transaction 1+ 23 56 2+ 3 56 12+ 3 56 1,4,7 3+ 56 3 ,6, 9...

Ngày tải lên: 15/03/2014, 09:20

... viable candidate, then it can be obtained by merging w with < {1} {2 6} {5}> © Tan,Steinbach, Kumar Introduction to Data Mining 37 GSP Example © Tan,Steinbach, Kumar Introduction to Data Mining ... 0. 17 = 0.9 Sup(W1, W2, W3) = + + + + 0. 17 = 0. 17 © Tan,Steinbach, Kumar Introduction to Data Mining 20 Multi-level Association Rules Food Electronics Bread Computer...

Ngày tải lên: 15/03/2014, 09:20

... Tan,Steinbach, Kumar Introduction to Data Mining Partitional Clustering Original Points © Tan,Steinbach, Kumar A Partitional Clustering Introduction to Data Mining Hierarchical Clustering p1 p2 Traditional ... e.g., autocorrelation Dimensionality Noise and Outliers Type of Distribution © Tan,Steinbach, Kumar Introduction to Data Mining 18 Clustering Algorithms K-m...

Ngày tải lên: 15/03/2014, 09:20

... Density Introduction to Data Mining 33 SNN Clustering Can Handle Differing Densities Original Points © Tan,Steinbach, Kumar SNN Clustering Introduction to Data Mining 34 SNN Clustering Can Handle ... merge (c) and (d) Introduction to Data Mining 13 Chameleon: Clustering Using Dynamic Modeling Adapt to the characteristics of the data set to find the natural clus...

Ngày tải lên: 15/03/2014, 09:20

... is obvious The present lecture note on Air pollution is therefore, prepared to be used as a teaching material to train mainly environmental health and other students of health category in Ethiopia ... Industrial Air Pollution 84 4.1 Learning Objective 84 4.2 Introduction to the Chapter 84 4.3 Types of Industrial Air Pollutants 85 4.4 Air Pollution from Industrial Accidents...

Ngày tải lên: 15/03/2014, 16:20

... Contents Up: Lecture Notes for CS 2110 Introduction to Theory Previous: Lecture Notes for CS 2110 Introduction to Theory Bob Daley 200 1-1 1-2 8 ©Copyright 1996 Permission is granted for personal ... Completeness http://www.cs.pitt.edu/ ~daley/ cs2110 /notes/ cs2110w.html (2 of 3) [12/23/2006 12:00:41 PM] Lecture Notes for CS 2110 Introduction to T...

Ngày tải lên: 12/05/2014, 04:36

... k(k + 2) 1 − k k+2 for any positive integer k, so 1 1 1 + + + + + 15 35 63 99 14 3 1 1 1 + + + + + = × 3 × 5 × 7 × 9 × 11 11 × 13 1 1 1 = − + − + ··· + − 3 11 13 1 = × 1 = 13 13 Example 10 If ab ... 3x 5x − (1 + 3x) 15 − 2x + 16 − 2x =1 = = , 1 15 15 15 10 − 6x x 14 x − (10 − 6x) 10 − 13 x x 2x − − = − = , 2 14 14 x− it follows that 16 − 2x 10 − 13...

Ngày tải lên: 11/03/2014, 16:55

... These lecture notes are copyrighted by Michael Creel with the date that appears above They are provided under the terms of the GNU General Public License, which forms Section 25 of the notes ... editable form for your version of the notes 1.2 Obtaining the notes These notes are part of the OMEGA (Open-source Materials for Econometrics, GPL Archive) project at pareto.uab.es/om...

Ngày tải lên: 08/04/2014, 12:28

... introduced because in General Relativity it is space itself which expands [19] Even though this equation is derived for matter, it is also true for radiation (In fact it is also true for vacuum, with ... Contravariant and covariant vectors are the dual of each other Other examples of dual spaces are row and column x matrices (x y) and and the kets < a| and bras |a > used in...

Ngày tải lên: 24/04/2014, 17:07

Ngày tải lên: 24/11/2014, 02:01