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Orange - Data Mining Fruitful & Fun

Orange - Data Mining Fruitful & Fun

http://orange.biolab.si/

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5 of the Best Free and Open Source Data Mining Software The process of extracting patterns from data is called data mining. It is recognized as an essential tool by modern business since it is able to convert data into business intelligence thus giving an informational edge. At present, it is widely used in profiling practices, like surveillance, marketing, scientific discovery, and fraud detection. There are four kinds of tasks that are normally involve in Data mining: * Classification - the task of generalizing familiar structure to employ to new data* Clustering - the task of finding groups and structures in the data that are in some way or another the same, without using noted structures in the data.* Association rule learning - Looks for relationships between variables.* Regression - Aims to find a function that models the data with the slightest error. For those of you who are looking for some data mining tools, here are five of the best open-source data mining software that you could get for free:

PyBrain Videos This video presentation was shown at the ICML Workshop for Open Source ML Software on June 25, 2010. It explains some of the features and algorithms of PyBrain and gives tutorials on how to install and use PyBrain for different tasks. This video shows some of the learning features in PyBrain in action. Data Visualization: Modern Approaches « Smashing Magazine About The Author Vitaly Friedman loves beautiful content and doesn’t like to give in easily. When he is not writing or speaking at a conference, he’s most probably running … More about Vitaly Friedman … Data presentation can be beautiful, elegant and descriptive. R Commander John Fox and Milan Bouchet-Valat Please Read the Rcmdr Installation Notes (click on the image for a larger view) For more details, see my paper on the R Commander in the Journal of Statistical Software (which is somewhat out of date) and the introductory manual distributed with the package (accessible via the Help -> Introduction to the R Commander menu). The R-Commander GUI consists of a window containing several menus, buttons, and information fields.

Weka 3 - Data Mining with Open Source Machine Learning Software in Java Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization.

Data Mining Image: Detail of sliced visualization of thirty video samples of Downfall remixes. See actual visualization below. As part of my post doctoral research for The Department of Information Science and Media Studies at the University of Bergen, Norway, I am using cultural analytics techniques to analyze YouTube video remixes. My research is done in collaboration with the Software Studies Lab at the University of California, San Diego.

Projects matching python. About: BayesOpt is an efficient, C++ implementation of the Bayesian optimization methodology for nonlinear-optimization, experimental design and stochastic bandits. In the literature it is also called Sequential Kriging Optimization (SKO) or Efficient Global Optimization (EGO). There are also interfaces for C, Matlab/Octave and Python. XmdvTool Home Page: Overview Overview XmdvTool is a public-domain software package for the interactive visual exploration of multivariate data sets. It is available on all major platforms such as UNIX, LINUX, MAC and Windows. Home - SCaVis Freedom to choose a programming language. Freedom to choose an operating system. Freedom to share your code. Enjoy the freedom of SCaVis. Supported programming languages

Eureqa Eureqa is a breakthrough technology that uncovers the intrinsic relationships hidden within complex data. Traditional machine learning techniques like neural networks and regression trees are capable tools for prediction, but become impractical when "solving the problem" involves understanding how you arrive at the answer. Eureqa uses a breakthrough machine learning technique called Symbolic Regression to unravel the intrinsic relationships in data and explain them as simple math. Using Symbolic Regression, Eureqa can create incredibly accurate predictions that are easily explained and shared with others. Over 35,000 people have relied on Eureqa to answer their most challenging questions, in industries ranging from Oil & Gas through Life Sciences and Big Box Retail.

projects:lasvm [Léon Bottou] 1. Introduction LASVM is an approximate SVM solver that uses online approximation. It reaches accuracies similar to that of a real SVM after performing a single sequential pass through the training examples. Further benefits can be achieved using selective sampling techniques to choose which example should be considered next.

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