data analysis findings discussion and some recommendations

Data Analysis Machine Learning and Applications Episode 3 Part 9 docx

Data Analysis Machine Learning and Applications Episode 3 Part 9 docx

... 593 Manni, Franz, 645 March, Nicolas, 439 Marinho, Leandro B., 533 Mehler, Alexander, 653 Meinl, Thorsten, 319 Meißner, Martin, 447 Merkel, Andreas, 553 Messaoud, Amor, 455 Meyer, David, 389 Meyer-Delius, ... Rosaria, 687 Rousson, Valentin, 209 Ruhland, Johannes, 327 Najman Migda , Kamila, 45 Najman, Krzysztof, 45 Naumann, Sven, 637 Nerbonne, John, 645 Neumann, Andreas W., 541 Nunkesser, Robin, 277 ... Klaus B., 515 Schettlinger, Karen, 277 Schierle, Martin, 397 Schiffner, Julia, 69 Schliep, Alexander, 119 Schmidt-Thieme, Lars, 171, 525, 533 Scholz, Sören W., 447 Schröder, Jan, 355 Schulz,...

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Data Analysis Machine Learning and Applications Episode 1 Part 1 doc

Data Analysis Machine Learning and Applications Episode 1 Part 1 doc

... Lechevallier, and O Opitz (Eds.) Ordinal and Symbolic Data Analysis 1996 M Schwaiger and O Opitz (Eds.) Exploratory Data Analysis in Empirical Research 2003 R Klar and O Opitz (Eds.) Classification and ... Schader, W Gaul, and M Vichi (Eds.) Between Data Science and Applied Data Analysis 2003 C Hayashi, N Ohsumi, K Yajima, Y Tanaka, H.-H Bock, and Y Baba (Eds.) Data Science, Classifaction, and Related ... 1998 H.-H Bock, M Chiodi, and A Mineo (Eds.) Advances in Multivariate Data Analysis 2004 I Balderjahn, R Mather, and M Schader (Eds.) Classification, Data Analysis, and Data Highways 1998 D Banks,...

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Data Analysis Machine Learning and Applications Episode 1 Part 2 potx

Data Analysis Machine Learning and Applications Episode 1 Part 2 potx

... training data set with 3000 and a test data set containing 1000 observations 3.2 Results We apply the local classification methods and global LDA to the simulated data sets and obtain 1280 test data ... recognition and machine learning communities due to the modularity of the algorithms and the data representations by kernel functions, cf (Schölkopf and Smola (2002)) and (Shawe-Taylor and Cristianini ... Distributions 1, Models and Applications, 2nd edition John Wiley & Sons, New York NEWMAN, D.J and HETTICH, S and BLAKE, C.L and MERZ, C.J (1998): UCI Repository of machine learning databases [http://www.ics.uci.edu/∼learn/...

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Data Analysis Machine Learning and Applications Episode 1 Part 3 docx

Data Analysis Machine Learning and Applications Episode 1 Part 3 docx

... well-known in data analysis (Chandon and Pinson (1971)) The motivation for using this similarity instead of the traditional Euclidean-based distance is twofold: (a) it is self-normalised, and (b) it ... References BERG, C CHRISTENSEN, J.P.R and RESSEL, P (1984): Harmonic Analysis on Semigroups: Theory of Positive Definite and Related Functions, Springer CHANDON, J.L and PINSON, S (1981): Analyse Typologique ... k = and k = −1, or k = −1 and k = This problem can be solved in a similar way as the original SVM Problem using the SMO algorithm (Schoelkopf and Smola 2002)(Zapien et al 2007), and adding some...

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Data Analysis Machine Learning and Applications Episode 1 Part 4 pptx

Data Analysis Machine Learning and Applications Episode 1 Part 4 pptx

... for discrimination of mixed data, Biometrics, 48, 497-506 Identification of Noisy Variables for Nonmetric and Symbolic Data in Cluster Analysis Marek Walesiak and Andrzej Dudek Wroclaw University ... interval data differs in steps and 2: A symbolic data array containing n objects and m symbolic interval variables is a starting point Identification of Noisy Variables for Nonmetric and Symbolic Data ... motions and parallaxes for the full set of sources This leads to a distinction for the data processing between early mission data, consisting of the spectra and positions, and late mission data, ...

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Data Analysis Machine Learning and Applications Episode 1 Part 5 pdf

Data Analysis Machine Learning and Applications Episode 1 Part 5 pdf

... classification and is pervasive in observational data, the techniques of ultrametric analysis and p-adic geometry are at ones disposal for identifying and exploiting ultrametricity A p-adic encoding of data ... some data set M which assigns to each x ∈ M a p-adic representation of an integer including and 1, yields a p-adic dendrogram D(M ∪ { }) whose root is v(0, 1, ), and any dendrogram for real data ... ultrametric spaces, and ultrametricity is a pervasive property of observational data, and by Murtagh (2004a) this offers computational advantages and a well understood basis for developping data processing...

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Data Analysis Machine Learning and Applications Episode 1 Part 6 docx

Data Analysis Machine Learning and Applications Episode 1 Part 6 docx

... procedure in data analysis: new results and open problems In: H H Bock, editor, Classification and related methods of data analysis North-Holland, Amsterdam, 309–316 BOORMAN, S A and ARABIE, P ... Stochastic Models and Data Analysis, 4, 273–282 154 Kurt Hornik and Walter Böhm GORDON, A D and VICHI, M (1998): Partitions of partitions Journal of Classification, 15, 265–285 GORDON, A D and VICHI, ... Conference on Knowledge Discovery and Data Mining (KDD-2004) COHEN, W W and RICHMAN, J (2002): Learning to Match and Cluster Large HighDimensional Data Sets for Data Integration In: Proceedings...

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Data Analysis Machine Learning and Applications Episode 1 Part 7 doc

Data Analysis Machine Learning and Applications Episode 1 Part 7 doc

... Zio and Ugo Guarnera lows to treat continuous and ordinal data, and in some circumstances also categorical variables However, in Paddok’s paper it is shown that, even with nonnormal data, in some ... in the data set not carry meaningful information about the genotypes and vice versa Discussion The clustering of geno- and phenotype data separately yielded interesting partitions of the data For ... Stalactite plots and robust estimation for the detection of multivariate outliers In: E Ronchetti, E Morgenthaler, and W Stahel (Eds.): New Directions in Statistical Data Analysis and Robustenss.,...

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Data Analysis Machine Learning and Applications Episode 1 Part 8 ppsx

Data Analysis Machine Learning and Applications Episode 1 Part 8 ppsx

... comprise some sort of regression models After presenting data and objectives (section 2) we outline methodology and results (section 3) and finally give some conclusions (section 4) Data and objectives ... Complementary use of correspondence analysis and cluster analysis In: Greenacre, M.J and Blasius, J (Eds.): Correspondence Analysis in the Social Sciences LEBART, L., MORINEAU, A and WARWICK, K (1984): Multivariate ... contingency tables and/ or the analysis of the table obtained as juxtaposition of the initial tables (Cazes (1980) and (1981)) and the Intra Analysis (Escofier (1983)) Nevertheless, in Zárraga and Goitisolo...

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Data Analysis Machine Learning and Applications Episode 1 Part 9 doc

Data Analysis Machine Learning and Applications Episode 1 Part 9 doc

... Republic, Denmark, Finland, France, Germany, Ireland, Italy, Netherlands, Norway, Poland, Portugal, Sweden and United Kingdom The scientific fields in which they are studying are: Social and Legal Sciences, ... Social and Legal Sciences Area have a different behavior The Netherlands and Ireland are selected as destiny country by males and females but males also go to Belgium, the United Kingdom and Italy ... Vanacore and Jean-Francỗois Durand limits (Wu and Wang, 1997; Jones and Woodall, 1998; Liu and Tang, 1996) has been followed Multivariate control charts based on projection methods A standard multivariate...

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Data Analysis Machine Learning and Applications Episode 1 Part 10 ppt

Data Analysis Machine Learning and Applications Episode 1 Part 10 ppt

... contingency tables In: R Coppi and S Bolasco (Eds.): Multiway Data Analysis North Holland, 301–314 LIGHT, R J and MARGOLIN, B H (1971): An analysis of variance for categorical data Journal of the American ... Fathers and Sons Biometrika, 3, 4, 467–469 ROUSSON, V and GASSER, Th (2004): Simple component analysis Applied Statistics, 53, 539–555 TENENHAUS, M and YOUNG, F.W., (1985): An analysis and synthesis ... L and stop ˆ Otherwise let S = S − SL(L SL)−1 L S and go back to step Father’s and son’s occupations data To illustrate the technique of Simple NSCA, we applied it to the well known Father’s and...

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Data Analysis Machine Learning and Applications Episode 2 Part 1 pot

Data Analysis Machine Learning and Applications Episode 2 Part 1 pot

... References ANDERSON, C R., DOMINGOS, P and WELD, D A (2002): Relational Markov models and their application to adaptive web navigation Proc of the International Conference on Knowledge Discovery and Data ... xdel Search in X for xdel and determine its rank i and the elements bs and bg pointed at Determine y( j) and y( ) with the help of the pointers such that bs = x(i) + y( j) and bg = x(i) + y( ) Find ... recovered for the first third of the second data set in the right-hand 282 Robin Nunkesser, Karen Schettlinger and Roland Fried side figure The trends in the second data set cause B to be in an additional,...

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Data Analysis Machine Learning and Applications Episode 2 Part 2 ppsx

Data Analysis Machine Learning and Applications Episode 2 Part 2 ppsx

... label A and can only be accepted by Sa () and Sb () The third temporal interval has label B and can be accepted by Sc () and Sd () It also stands to the first A in the relation after and to the ... 2001), FSG (Kuramochi and Karypis 2001), MoSS/MoFa (Borgelt and Berthold 2002), gSpan (Yan and Han 2002), Closegraph (Yan and Han 2003), FFSM (Huan et al 2003), and Gaston (Nijssen and Kok 2004) A ... conduct the Wald test for and : W = ˆ / ˆ and W = ˆ / ˆ , where ˆ and ˆ are the estimates of the general model under consideration, and ˆ and ˆ are the estimated standard errors thereof Note...

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Data Analysis Machine Learning and Applications Episode 2 Part 3 pps

Data Analysis Machine Learning and Applications Episode 2 Part 3 pps

... segmentation and classification results obtained for the skin cancer data set and Section is devoted to discussions and conclusions Labelling Hyper-spectral data are highly correlated and contain ... stringranking() Candidate record pairs from data frames data1 and data2 are created and filtered according to the specified method (default: 'blocking') In case of a deduplication scenario, data2 does ... code of last name retains only 83 candidates > candidates (data1 =d1.prep, data2 =d2.prep, method='blocking',selvars1='asoundex.lname') > candidates (data1 =d1.prep, data2 =d2.prep, method='sorted', selvars1=c...

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Data Analysis Machine Learning and Applications Episode 2 Part 4 doc

Data Analysis Machine Learning and Applications Episode 2 Part 4 doc

... end for 7: for i = to n AND j = to n − AND k = j + to n 8: if i != j AND i != k then 9: set Z := data[ ,j] · data[ ,k] 10: estimation by lm (data[ ,i] Z) 11: if significant AND parameter estimates ... quantitative analysis of the map (Vesanto and Alhoniemi (2000), Lemaire and Clérot (2005)) For a complete description of the SOM properties and some applications, see (Kohonen (2001)) and (Oja and Kaski ... describe how data mining techniques applied to network measurement data can help to extract some qualitative and quantitative knowledge Introduction Broadband access for home users and small or...

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Data Analysis Machine Learning and Applications Episode 2 Part 5 pps

Data Analysis Machine Learning and Applications Episode 2 Part 5 pps

... scheme of exploratory data analysis has been presented to give lightings on the usages of applications and daily traffic profiles Our data- mining approach, based on the analysis and the interpretation ... calculated and the most likely word is applied A more detailed introduction into context-based spelling correction can be found in Golding and Roth (1995), Golding and Roth (1999) and Al-Mubaid and ... parameter settings and dataset characteristics We believe that this discussion may be of interest to anyone who may want to use this database for their own purposes, or set up a similar databases for...

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Data Analysis Machine Learning and Applications Episode 2 Part 6 potx

Data Analysis Machine Learning and Applications Episode 2 Part 6 potx

... e.eid and e.learner_inst = li.liid and li.lid = l.lid and l.name='A' and lv.liid=li.liid and lv.pid = lp.pid and lp name='P' and e .data_ inst = di.diid and di.did = d.did and d.name='D' Sometimes ... learner l, data_ inst di, dataset d, evaluation v WHERE v.eid = e.eid and e.learner_inst = li.liid and li.lid = l.lid and l.name='A' and e .data_ inst = di.diid and di.did = d.did 4.4 Applying data mining ... connector, CSV and ARFF writer, Excel spreadsheet writer Data manipulation: row and column filtering, data partitioning and sampling, sorting or random shuffling, data joiner and merger Data transformation:...

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Data Analysis Machine Learning and Applications Episode 2 Part 7 docx

Data Analysis Machine Learning and Applications Episode 2 Part 7 docx

... mobility multimodal distribution Decision Boundaries C1: Data ≤ C2: Data > C1: Data ≤ C2: Data > C1: Data ≤ C2: Data > C1: Data ≤ C2: < Data < 50 C3: Data ≥ 50 Size of Classes [5820], 46,82% [6610], ... in Analysis of Social Network Data In: M Schwaiger, and O Opitz (Eds.): Exploratory Data Analysis in Empirical Research Springer, Berlin, 149-156 SCOTT, J (1991): Social Network Analysis: A Handbook ... Social Network Analysis: Methods and Applications Cambridge University Press, Cambridge WRIGHT, B and EVITTS, M.S (1961): Direct Factor Analysis in Sociometry Sociometry, 24, 82–98 Urban Data Mining...

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Data Analysis Machine Learning and Applications Episode 2 Part 8 docx

Data Analysis Machine Learning and Applications Episode 2 Part 8 docx

... guidelines of data protection, the whole process uses anonymous data and is optimised by the aggregation per regional level to the principles of data- avoidance and data- economy (Steckler and Pepels ... Adaptive Conjont Analysis: Understanding the Methodology and Assessing Reliability and Validity In: A Gustafsson, A Herrmann and F Huber (Eds.): Conjoint Measurement: Methods and Applications, ... organisation) and in order to reduce complexity in multivariate data- structures we derive relevant customer insight from the huge amount of data and aggregate the data to the relevant SCCD CLV, CLC and...

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Data Analysis Machine Learning and Applications Episode 2 Part 9 pdf

Data Analysis Machine Learning and Applications Episode 2 Part 9 pdf

... support all-confidence {brandy, whisky} 0.011 0.23 {brandy, fruit brandy} 0.015 0.18 {fruit brandy, appetizers} 0.018 0.17 {brandy, appetizers} 0.016 0.15 {whisky, fruit brandy} 0.011 0.14 To examine ... introduced and criteria for determining the number of clusters in the data are discussed The data and the results of this study are outlined in section 4, and section concludes with a discussion ... or CAIC (Andrews and Currim (2003)) Classifying Contemporary Marketing Practices 493 Empirical application 4.1 Data description and preprocessing The data are gathered in using the standardized...

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