difference between data information and knowledge by giving examples

in prostate tests psa what is the difference between total psa and free psa

... method. Differences between test and comparison methods were estimated at 2.5, 4.0, and 10.0 ng/mL (2.5, 4.0, and 10.0 µg/L) for tPSA and 15%, 20%, and 25% for percentage of fPSA. Relative differences ... total PSA level between 4 ng/ml and 10 ng/ml. A PSA level of 4 to 10 ng/ml is considered slightly elevated levels between 10 and 20 ng/ml are considered moderately elevated; and anything above ... diagnosis and treatment of any and all medical conditions.I add a link with details of this subjecthttp://www.labtestsonline.org.uk/ understanding/analytes/psa/test.htmlIntermethod Differences...

Advanced Information and Knowledge Processing ppt

Danh mục: Sức khỏe giới tính

... informatics is the study, development, and implementation of al-gorithms and systems to improve communication, understanding, and man-agement of medical knowledge and data. It is a multi-disciplinary ... asthe test set.6 Dirk Husmeierθ^θ Data Data1θ^θ^θ^ ..θ Data 21 Data M2MFig. 1.3. The frequentist paradigm. Left: Data are generated by some processwith true, but unknown ... ofInfection,andPathogens 45415.3.1 PatientExample(Part1) 45415.3.2 Fusion of Data and Knowledge for Calculation ofProbabilities for Sepsis and Pathogens 45615.4 CalculationofCoverage and TreatmentAdvice...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 130 doc

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... 1189 Data cleaning, 19, 615 Data collection, 1084 Data envelop analysis (DEA), 968 Data management, 559 Data mining, 1082 Data Mining Tools, 1155 Data reduction, 126, 349, 554, 566, 615 Data ... the data is is a very important part of Data Mining, and many data visualization facilities and data preprocessing tools are provided. All algorithms and methods take their input in the form ... agricultural data, motivated by the importance of this application area in New Zealand. However, the machine learning meth-ods and data engineering capability it embodies have grown so quickly, and so...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 1 pps

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... RokachEditors Data Mining and Knowledge Discovery HandbookSecond Edition123Contents1 Introduction to Knowledge Discovery and Data MiningOded Maimon, Lior Rokach 1Part I Preprocessing Methods2 Data ... challenge created by today’s abundance of data. Knowledge Discovery in Databases (KDD) is the process of identifying valid,novel, useful, and understandable patterns from large datasets. Data Mining ... neural networks, and evolutionary algorithms.Parts ﬁve and six present supporting and advanced methods in Data Mining, suchas statistical methods for Data Mining, logics for Data Mining, DM...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 2 pptx

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... Multimedia Data Mining58 Data Mining in MedicineNada Lavraˇc, Blaˇz Zupan 111159 Learning Information Patterns in Biological Databases - Stochastic Data MiningGautam B. Singh 113760 Data Mining ... Rokach 95951 Data Mining using Decomposition MethodsLior Rokach, Oded Maimon 98152 Information Fusion - Methods and Aggregation OperatorsVicenc¸ Torra 99953 Parallel And Grid-Based Data Mining ... 75940 Mining Concept-Drifting Data StreamsHaixun Wang, Philip S. Yu, Jiawei Han 78941 Mining High-Dimensional Data Wei Wang, Jiong Yang 80342 Text Mining and Information ExtractionMoty Ben-Dov,...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 3 pptx

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... understanding phenomena from the data, analysis and prediction.The accessibility and abundance of data today makes Knowledge Discovery and Data Mining a matter of considerable importance and necessity. ... theinteractive and iterative aspect of the KDD is taking place. It starts with thebest available data set and later expands and observes the effect in terms of knowledge discovery and modeling.3. ... Starting from the data sources (such as operational databases, semi- and non-structured data and reports, Internet sites etc.), the ﬁrst tier is the data warehouse,followed by OLAP (On Line...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 4 ppsx

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... X. and Kumar, V. and Ross Quinlan, J. and Ghosh, J. and Yang, Q. and Motoda, H. and McLachlan, G.J. and Ng, A. and Liu, B. and Yu, P.S. and others, Top 10 algorithms in data mining, Knowledge and ... Mining and Knowledge Discovery, 15(1):87-97, 2007.Larose, D.T., Discovering knowledge in data: an introduction to data mining, John Wiley and Sons, 2005.Maimon O., and Rokach, L. Data Mining by ... Knowledge and Information Systems, 14(1): 1–37, 2008.14 Oded Maimon and Lior RokachAverbuch, M. and Karson, T. and Ben-Ami, B. and Maimon, O. and Rokach, L., Context-sensitive medical information...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 5 pptx

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... analyze, and investigate such very large data sets hasgiven rise to the ﬁelds of Data Mining (DM) and data warehousing (DW). Withoutclean and correct data the usefulness of Data Mining and data ... examiningdatabases, detecting missing and incorrect data, and correcting errors. Other recentwork relating to data cleansing includes (Bochicchio and Longo, 2003, Li and Fang,1989). Data Mining ... areasthat include data cleansing as part of their deﬁning processes are: data warehousing, knowledge discovery in databases, and data/ information quality management (e.g.,Total Data Quality Management...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 6 ppt

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... Data Warehousing and Knowledge Discovery; 2002 September 04-06; 170-180.Hernandez, M. & Stolfo, S. Real-world Data is Dirty: Data Cleansing and The Merge/PurgeProblem, Data Mining and Knowledge ... Methods, Data Mining and Knowledge Discov-ery Handbook, Springer, pp. 321-352.Simoudis, E., Livezey, B., & Kerber, R., Using Recon for Data Cleaning. In Advances in Knowledge Discovery and Data ... France. 464-467.Brachman, R. J., Anand, T., The Process of Knowledge Discovery in Databases — AHuman–Centered Approach. In Advances in Knowledge Discovery and Data Min-ing, Fayyad, U. M., Piatetsky-Shapiro,...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 7 ppsx

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... yi,1ifx and y are symbolic and xi= yi,or xi=?oryi=?,|xi−yi|rif xi and yiare numbers and xi= yi,where r is the difference between the maximum and minimum of the known valuesof ... other methods to handle missing attribute values. One of them isevent-covering method (Chiu and Wong, 1986), (Wong and Chiu, 1987), based on aninterdependency between known and missing attribute ... (Latkowski, 2003, Latkowski and Mikolajczyk, 2004). In this method a data set isdecomposed into complete data subsets, rule sets are induced from such data subsets, and ﬁnally these rule sets...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 8 potx

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... Multivariate Data. Chapman and Hall, London, 1997.Slowinski R. and Vanderpooten D. A generalized deﬁnition of rough approximations basedon similarity. IEEE Transactions on Knowledge and Data Engineering ... 4 (2002) 21 – 30.Wu X. and Barbara D. Modeling and imputation of large incomplete multidimensionaldatasets. Proc. of the 4-th Int. Conference on Data Warehousing and Knowledge Dis-covery, Aix-en-Provence, ... incomplete information databases. ACM Transactions on Database Systems 4 (1979), 262–296.Lipski W. Jr. On databases with incomplete information. Journal of the ACM 28 (1981) 41–70.Little R.J.A. and...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 9 pdf

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... right hand side where d m and d > r, and ap-proximate the eigenvector of the full kernel matrix Kmm by evaluating the left handrows (and hence columns) are linearly independent, and suppose ... orvideo data) and to make the features more robust. The above features, computed by taking projections along the n’s, are ﬁrst translated and normalized so that the signal data has zero mean and ... KCij≡(Φi−μ)·(Φj−μ). Happily, any m by m dot product matrix can be centered by left- and right- multiplying by the projection matrix P ≡ 1 −1mee, where 1 is the unitmatrix in Mm and where e is the m-vector...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 10 ppt

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... simple mapping from a dataset to an undirectedgraph G by forming a one-to-one correspondence between nodes in the graph and data points. If two nodes i, j are connected by an arc, associate with ... (Silva and Tenenbaum, 2002). Landmark Isomap simply employs land-mark MDS (Silva and Tenenbaum, 2002) to addresses this problem, computing alldistances as geodesic distances to the landmarks. ... distances; by contrast, LLE, spectral clustering and Laplacian eigen-maps are local (for example, LLE attempts to preserve local translations, rotations and scalings of the data) . Landmark Isomap...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 11 pdf

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... feature as irrelevant and redundant information. The process of feature selection reduces the dimensionality of the data and enables learning algorithms to operate faster and more effectively. ... 2001.Y. LeCun and Y. Bengio. Convolutional networks for images, speech and time-series. InM. Arbib, editor, The Handbook of Brain Theory and Neural Networks. MIT Press, 1995.M. Meila and J. Shi. ... segmentation by random walks.In Advances in Neural Information Processing Systems, pages 873–879, 2000.S. Mika, B. Schölkopf, A. J. Smola, K R. Müller, M. Scholz, and G. Rätsch. Kernel PCAand...

Data Mining and Knowledge Discovery Handbook, 2 Edition part 12 ppsx

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... Kaufmann, 1996.Maimon O., and Rokach, L. Data Mining by Attribute Decomposition with semiconductorsmanufacturing case study, in Data Mining for Design and Manufacturing: Methods and Applications, D. ... pp. 178-196, 2002.Maimon, O. and Rokach, L., Decomposition Methodology for Knowledge Discovery and Data Mining: Theory and Applications, Series in Machine Perception and Artiﬁcial In-telligence ... the average size of the trees produced by C4.5 (normalized by the number oftraining examples) , and F is the number of features is the subset X (normalized by the total number of available features)....