curso de KNIME
Posted by Armando Brito Mendes | Filed under mapas SIG's, materiais para profissionais, software, videos, visualização
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Muito bom curso de KNIME, é introdutório mas introduz um grande número de funcionalidades.
KNIME Online Self-Training
Welcome to the KNIME Self-training course. The focus of this document is to get you started with KNIME as quickly as possible and guide you through essential steps of advanced analytics with KNIME. Optional and very useful topics such as reporting, KNIME Server and database handling are also included to give you an idea of what else is possible with KNIME.
- Installing KNIME Analytics Platform and Extensions
- Data Import / Export and Database / Big Data
- ETL
- Visualization
- Advanced Analytics
- Reporting
- KNIME Server
Tags: análise de dados, big data, data mining, Knime, text mining
KNIME Community Contributions
Posted by Armando Brito Mendes | Filed under materiais para profissionais, software
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Boa fonte de novos nós do KNIME, evitando q estejamos a programar algo q já foi programado antes.
KNIME Community Contributions offer a wide range of KNIME nodes from different application areas, such as chemo- and bioinformatics, image processing, or information retrieval. In contrast to the extensions available via the standard KNIME Update Site they are provided and maintained by various community developers.
The Trusted Community Contributions can easily be installed by selecting File -> Install KNIME Extensions in KNIME. Additional extensions are available by enabling the Update Site in KNIME via File -> Preferences -> Install/Update -> Available Update Sites. See the update site guide for details.
You can also download the whole update site as a ZIP archive and add the ZIP to the Available Update Sites (see above).
Tags: data mining, Knime, software estatístico, text mining
KNIME Update Site
Posted by Armando Brito Mendes | Filed under materiais ensino, software
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Formas alternativas de instalar novos nós no KNIME
Download KNIME Features using the KNIME Update Site
Additional KNIME plug-ins can be obtained via the KNIME update site which contains additional nodes/functionality for the KNIME workbench:
http://update.knime.org/analytics-platform/2.12/
Alternatively, the KNIME update sites can be downloaded as a zip file:
The KNIME Analytics Platform as well as all other KNIME products are linked automatically to the KNIME Update Site through the File menu via the “Install KNIME Extensions” command. We recommend using this command to access the KNIME Update Site.
If you are using KNIME SDK, a pre-existing Eclipse installation, or are working in an environment with limited internet access, another option for installing KNIME extensions is available. To access this additional dialog use the Help -> Install New Software command. This tool has a different interface that allows update sites to be manually specified. Clicking on “Add…” button (illustrated below) will allow you to either manually specify the url of the KNIME Update Site or use the offline (.zip) version of the Update Site to customize your KNIME installation.
Note: It is important not to unzip the archived KNIME Update Site file prior to specifying it as an update source for KNIME.
Tags: data mining, Knime
KNIME Image Processing (trusted extension)
Posted by Armando Brito Mendes | Filed under videos, visualização
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Apenas um exemplo das fantásticas possibilidades do KNIME
KNIME Image Processing (trusted extension)
Fri, 12/03/2010 – 13:09 — knime_admin
Overview
The KNIME Image Processing Plugin allows you to read in more than 120 different kinds of images (thanks to the Bio-Formats API) and to apply well known methods on images, like preprocessing. segmentation, feature extraction, tracking and classification in KNIME. In general these nodes operate on multi-dimensional image data (e.g. videos, 3D images, multi-channel images or even a combination of them), which is made possible by the internally used ImgLib2-API.
Several nodes are available to calculate image features (e.g. zernike-, texture- or histogram features) for segmented images (e.g. a single cell). These feature vectors can then be used to apply machine learning methods in order to train and apply a classifier.
Currently the Image Processing Plugin for KNIME provides ca. 100 nodes for (pre)-processing, filtering, segmentation, feature extraction, various views (2D, 3D), etc. and integrations for various other image processing tools are available (see used and integrated libraries)
Future directions include a full, bidirectional integration of ImageJ2. Such an integration allow the users to use directly use/update ImageJ2 Plugins inside KNIME as well as recording and running KNIME Workflows in ImageJ2. Please see ImageJ2 Integration (BETA) for more information.
For the first steps please consider the KNIME Image Processing User Manual (incomplete draft!).
Important Links
- How to install KNIME Image Processing?
- Example Workflows and Tutorials
- KNIME Image Processing Forum
- KNIME Image Processing (Webinar on YouTube)
- KNIME FAQ
- KNIME Image Processing on GitHub
- KNIME Image Processing News
- Contact
Tags: data mining, image mining, Knime
