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  • Orange Data Mining
    still available Features Interactive workflows Create your own interactive workflows to analyse and visualize your data Visualization Orange is packed with different visualizations from scatter plots bar charts trees to dendrograms networks and heat maps Large Toolbox Over 100 widgets and growing We cover most of standard data analysis tasks Specialized add ons available like Orange Bioinformatics Orange Screenshots License Privacy Policy Citation Contact Download Windows Mac OS Linux Community

    Original URL path: http://orange.biolab.si/ (2016-02-14)
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  • Orange Data Mining
    clustering Playing with a paint data and automatic selection of clusters in k means Feature scoring and ranking Model based feature scoring Polynomial regression Predictions of a linear regression model on a test set Data preprocessing turned into component of a learning algorithm Cross validation and scoring of classifiers Visualizing misclassifications Receiver operating characteristics ROC analysis Cross validated calibration plot Venn diagram identifies a missclassification Orange can guess which widget

    Original URL path: http://orange.biolab.si/screenshots/ (2016-02-14)
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  • Orange Data Mining
    bioinformatics readthedocs org Orange3 Associate version 1 0 0 Orange add on for enumerating frequent itemsets and association rules mining Orange3 DataFusion version 0 1 9 This is a data fusion add on for Orange3 http orange biolab si Add on wraps scikit fusion http github com marinkaz scikit fusion a Python library for data fusion and implements a set of widgets for loading of the data definition of data fusion schema collective matrix factorization and exploration of latent factors Installation To install the add on run python setup py install To register this add on with Orange but keep the code in the development directory do not copy it to Python s site packages directory run python setup py develop Usage Run Orange from the terminal by python m Orange canvas Data fusion widgets are in the toolbox bar under Data Fusion section Orange3 Network version 1 1 2 Orange Network is an add on for Orange data mining software package It provides network visualization and analysis tools Documentation is found at http orange network readthedocs org Orange3 Prototypes version 0 4 4 Prototype Orange widgets Only for the brave Orange3 Text version 0 1 9 NOTE This plug in currently could NOT be installed We are working on resolving the issue until then if curious you can install it from source https github com biolab orange3 text but beware that it is still in development Orange3 Text extends Orange with common functionality for text mining It provides access to publicly available data like NY Times Twitter and PubMed Further it provides tools for preprocessing constructing vector spaces like bag of words topic modeling and word2vec and visualizations like word cloud end geo map All features can be combined with powerful data mining techniques from the Orange data mining

    Original URL path: http://orange.biolab.si/download/ (2016-02-14)
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  • Orange Data Mining
    Widget Development Tutorial and Reference Orange Data Mining Library Tutorial and reference Orange Screenshots License Privacy Policy Citation Contact Download Windows Mac OS Linux Community Stack Exchange Facebook YouTube OrangeDataMiner Documentation Get started Widgets Scripting Developers GitHub Contribute Latest blog

    Original URL path: http://orange.biolab.si/docs/ (2016-02-14)
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  • Orange Data Mining
    enable users explore model maps Documentation is found at http orange modelmaps readthedocs org Orange Multitarget version 0 9 3 Orange Multitarget is an add on for Orange data mining software package It extends Orange by providing methods that allow for classification of datasets with multiple classes Currently supported techniques Binary Relevance Classifier Chains and Ensemble Classifier Chains Clustering Trees Neural Networks Partial Least Squares Documentation can be viewed at http orange multitarget readthedocs org Orange NMF version 0 1 2 Orange NMF is an add on for Orange data mining software package It provides non negative matrix factorization algorithms NMF through NIMFA and robust singular value decomposition rSVD It includes widgets that deal with missing data in input matrices their normalizations viewing and assessing the quality of matrix factors returned by different matrix factorization algorithms Documentation is found at https orange nmf readthedocs org Widgets were designed and implemented by Fajwel Fogel Ecole Polytechnique ParisTech All NMF methods call NIMFA library implemented by Marinka Zitnik Bioinformatics Laboratory FRI UL Thanks also to Doug Marsteller Stan Young NISS Chris Beecher Paul Fogel Orange Network version 0 3 4 Orange Network is an add on for Orange data mining software package It provides network visualization and analysis tools Documentation is found at http orange network readthedocs org Orange Reliability version 0 2 14 Orange Reliability is an add on for Orange data mining software package that enables the estimation of reliabilities for individual predictions Documentation http pythonhosted org Orange Reliability Orange Text version 1 2a1 Orange Text Mining is an add on for Orange data mining software package It extends Orange by providing common functionality for basic tasks in text mining Documentation is found at http orange text readthedocs org Orange Textable version 1 5 2 Orange Textable is an open

    Original URL path: http://orange.biolab.si/orange2/ (2016-02-14)
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  • Orange Data Mining
    other widgets Double click on the File widget icon to open it Select Browse documentation data sets and from the list of pre installed data files chose iris tab The File widget will now read the the famous data set on 150 Iris flowers and send it to the workflow The changes will propagate through the workflow updating its widgets Close the window of the File widget and double click on the Data Table widget to open it This displays the data that we have just read Open and close other widgets to see what they do In this workflow the most interesting widget is Hierarchical Clustering that displays clustering results Scroll through the dendrogram the tree based rendering of the clustering to check if the algorithm correctly identified the three species of Iris You may now open other tutorials from the Help menu choose Tutorials Or create a workflow of your own Your Own Workflow We first need to start with an empty canvas Click on New in Orange s welcome screen or if Orange is already running choose New from the File menu We will explore the data on passengers of the HMS Titanic and develop a model to predict the probability of survival based on the passenger s traveling class gender and age Let us start by placing the File and Data Table widgets on the canvas We would like the File widget to read the data and send it to the Data Table for inspection We need to connect these two widgets to establish a communication between them Click on the dashed line besides the File widget and drag the line to the Data Table To load the data open the File widget double click on its icon select Browse documentation data sets from the Data

    Original URL path: http://orange.biolab.si/getting-started/ (2016-02-14)
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  • Orange Data Mining
    Concatenate Paint Data Python Script Feature Constructor Edit Domain Image Viewer Impute Merge Data Outliers Preprocess Purge Domain Rank Box Plot Distributions Heat Map Scatter Plot Venn Diagram Linear Projection ModelMap Projection Rank Scatter Map Sieve Diagram Naive Bayes Logistic Regression Classification Tree Classification Tree Viewer Nearest Neighbors Load Classifier Majority Random Forest Save Classifier SVM Linear Regression Mean Learner Nearest Neighbors Stochastic Gradient Descent SVM Regression PCA Correspondence Analysis

    Original URL path: http://orange.biolab.si/toolbox/ (2016-02-14)
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  • Orange Data Mining
    Chih Chung Chang and Chih Jen Lin All rights reserved Redistribution and use in source and binary forms with or without modification are permitted provided that the following conditions are met 1 Redistributions of source code must retain the above copyright notice this list of conditions and the following disclaimer 2 Redistributions in binary form must reproduce the above copyright notice this list of conditions and the following disclaimer in the documentation and or other materials provided with the distribution 3 Neither name of copyright holders nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS AS IS AND ANY EXPRESS OR IMPLIED WARRANTIES INCLUDING BUT NOT LIMITED TO THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT INDIRECT INCIDENTAL SPECIAL EXEMPLARY OR CONSEQUENTIAL DAMAGES INCLUDING BUT NOT LIMITED TO PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES LOSS OF USE DATA OR PROFITS OR BUSINESS INTERRUPTION HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY WHETHER IN CONTRACT STRICT LIABILITY OR TORT INCLUDING NEGLIGENCE OR OTHERWISE ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE end libsvm copyright liblinear copyright Copyright c 2007 2009 The LIBLINEAR Project All rights reserved Redistribution and use in source and binary forms with or without modification are permitted provided that the following conditions are met 1 Redistributions of source code must retain the above copyright notice this list of conditions and the following disclaimer 2 Redistributions in binary form must reproduce the above copyright notice this list of conditions and the following disclaimer in the documentation and or other materials provided with the distribution 3 Neither name of copyright holders nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS AS IS AND ANY EXPRESS OR IMPLIED WARRANTIES INCLUDING BUT NOT LIMITED TO THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT INDIRECT INCIDENTAL SPECIAL EXEMPLARY OR CONSEQUENTIAL DAMAGES INCLUDING BUT NOT LIMITED TO PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES LOSS OF USE DATA OR PROFITS OR BUSINESS INTERRUPTION HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY WHETHER IN CONTRACT STRICT LIABILITY OR TORT INCLUDING NEGLIGENCE OR OTHERWISE ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE end liblinear copyright qhull copyright Qhull Copyright c 1993 2003 The National Science and Technology Research Center for Computation and Visualization of Geometric Structures The Geometry Center University of Minnesota email qhull qhull org This software includes Qhull from The Geometry Center Qhull is copyrighted as noted

    Original URL path: http://orange.biolab.si/license/ (2016-02-14)
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