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Category: Data Mining (page 2 of 40)

Pandas for Everyone: Python Data Analysis (Addison-Wesley

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Language: English

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Size: 6.22 MB

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It is a label for an activity performed in a wide variety of application domains within the science and business communities, as well as for pleasure. Otherwise, perhaps this will be helpful to others… The business problem to solve was generating customer insight (Businesses with loans), with considerations for each client business' financial health and business loan repayment risk. To our knowledge, PowerGet and FragmentAlign are the first tools to allow users to curate alignment results via GUI.

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Big Data: Concepts, Methodologies, Tools, and Applications

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Language: English

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Size: 8.80 MB

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This has once again proved to be a difficult task - despite the power of these new techniques and the similarities of their architecture to that of the human brain. If companies were to attempt to tackle big data software on their own, with no input or help from open-source softwares, it would be a painfully slow process. Preserving Data Mining Models and Algorithms. In this section, learn more about what works and what doesn't and get tips on which options are most suitable for your data processing, business intelligence and analytics needs.

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Cloud Computing: Methodology, Systems, and Applications

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Language: English

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Size: 9.31 MB

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IBM Watson Research Center They're great. Of course, the appeal to record labels is obvious, as it offers a rational underpinning for commercial decisions. Knowledge Discovery and Data Mining focuses on the process of extracting meaningful patterns from biomedical data (knowledge discovery), using automated computational and statistical tools and techniques on large datasets (data mining). For 2016, the source projects the global big data market is predicted to grow to more than 45 billion U.

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Practical Text Analytics: Interpreting Text and Unstructured

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Language: English

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Size: 12.97 MB

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The business data is also growing at these same exponential rate too. This means that biologists must learn to use cutting-edge computational technologies, but, as Zola says, that "puts a pressure on information technology experts to deliver efficient solutions that are easy to adopt by the domain experts, yet hide the complexity of the underlying algorithm, software, and hardware architecture without sacrificing the efficiency."

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Rule Based Systems for Big Data: A Machine Learning Approach

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Language: English

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Size: 8.44 MB

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AT&T, for example, recently introduced Sales & Marketing Solution Packs to mine data warehouses. If you want to scale up to "Hadoop size" on the long run, you will have to think about data layout and organization, too, unless all you need is a linear scan over the data. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles.

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New Trends of Research in Ontologies and Lexical Resources:

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Language: English

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Size: 11.82 MB

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Multimedia Data Mining Multimedia data types any type of information medium that can be represented, processed, stored and transmitted over network in digital form Multi-lingual text, numeric, images, video, audio, graphical, temporal, relational, and categorical data. 6/6/2010 2 Definitions Subfield of data mining that deals with an extraction of implicit knowledge, multimedia data relationships, or other patterns not explicitly stored in multimedia databases Influence on related interdisciplinary fields Databases – extension of the KDD (rule patterns) Information systems – multimedia information analysis and retrieval – content-based image and video search and efficient storage organization 6/6/2010 3 6/6/2010 5 Generalizing Spatial and Multimedia Data Spatial data: Generalize detailed geographic points into clustered regions, such as business, residential, industrial, or agricultural areas, according to land usage Require the merge of a set of geographic areas by spatial operations Image data: Extracted by aggregation and/or approximation Size, color, shape, texture, orientation, and relative positions and structures of the contained objects or regions in the image Music data: Summarize its melody: based on the approximate patterns that repeatedly occur in the segment Summarized its style: based on its tone, tempo, or the major musical instruments played 6/6/2010 6 Similarity Search in Multimedia Data Description-based retrieval systems Build indices and perform object retrieval based on image descriptions, such as keywords, captions, size, and time of creation Labor-intensive if performed manually Results are typically of poor quality if automated Content-based retrieval systems Support retrieval based on the image content, such as color histogram, texture, shape, objects, and wavelet transforms 6/6/2010 7 Multidimensional Analysis of Multimedia Data Multimedia data cube Design and construct similar to that of traditional data cubes from relational data Contain additional dimensions and measures for multimedia information, such as color, texture, and shape The database does not store images but their descriptors Feature descriptor: a set of vectors for each visual characteristic Color vector: contains the color histogram MFC (Most Frequent Color) vector: five color centroids MFO (Most Frequent Orientation) vector: five edge orientation centroids Layout descriptor: contains a color layout vector and an edge layout vector Mining Associations in Multimedia Data Associations between image content and non-image content features “If at least 50% of the upper part of the picture is blue, then it is likely to represent sky.” Associations among image contents that are not related to spatial relationships “If a picture contains two blue squares, then it is likely to contain one red circle as well.” Associations among image contents related to spatial relationships “If a red triangle is between two yellow squares, then it is likely a big oval-shaped object is underneath.” 6/6/2010 12 6/6/2010 13 Special features: Need occurrences besides Boolean existence, e.g., “Two red square and one blue circle” implies theme “air-show” Need spatial relationships Blue on top of white squared object is associated with brown bottom Need multi-resolution and progressive refinement mining It is expensive to explore detailed associations among objects at high resolution It is crucial to ensure the completeness of search at multi-resolution space Mining Associations in Multimedia Data

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Islam Dot Com (The Palgrave Macmillan Series in

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Language: English

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Size: 12.52 MB

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Data mining relies on information that is already available. Increasingly though, big data vendors are pushing the concept of a Hadoop data lake that serves as the central repository for an organization's incoming streams of raw data. When the classification part is tested it could be beneficial if they were to compare other methods to their hierarchal rule based temporal model. You can download a collection of 36 real-life datasets in ARFF format from the UCI machine learning repository.

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Microsoft SQL Server 2014 Business Intelligence Development

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Language: English

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Size: 11.09 MB

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Once the iterative search process is complete, the data-mining system generates report findings. Certainly statistics can do more than answer these questions but for most people today these are the questions that statistics can help answer. Most of the presentations and slideshows on PowerShow.com are free to view, many are even free to download. (You can choose whether to allow people to download your original PowerPoint presentations and photo slideshows for a fee or free or not at all.) Check out PowerShow.com today - for FREE.

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Intelligence in the Era of Big Data: 4th International

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Language: English

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Size: 12.88 MB

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Tutorial in AAAI 2011: Machine Learning in Time Series Databases (and Everything Is a Time Series!). 7th August 2011. Having a goal will create something to focus on. My research interests are mainly in cloud computing and database systems, including indexing, query processing and data management, especially for supporting write-intensive workloads. Tagging data is a necessary first step to data mining because it enables analysts (or the software they use) to classify and organize the information so it can be searched and processed.

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HCI International 2007: 12th International Conference, HCI

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Language: English

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Size: 10.93 MB

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Google Scholar Rolia J, Yao W, Basu S, Lee WN, Singhal S, Kumar A, Sabella S: Tell me what i don’t know - making the most of social health forums. At the request of the FBI, FISA Court judge Roger Vinson issued an order compelling the company to hand over its phone records. In this blog post, I will look at four different rankings of data mining journals and conferences based on different criteria, and discuss these rankings. This paper will present recent research using Big Data tools and approaches for the analysis of Health Informatics data gathered at multiple levels, including the molecular, tissue, patient, and population levels.

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