Search Results for "feature selection"
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Showing 17 open source projects for "feature selection"
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM... -
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Stipple Effect
A pixel art editor that supports animation and scripting
Stipple Effect is a pixel art editor that supports animation and scripting. It is designed to facilitate a variety of workflows and to encourage rapid, iterative creation of video game art assets and other types of artwork. Stipple Effect was made by a solo indie game developer with the needs and skill sets of other indie developers in mind. It is lightweight and simple to learn and use, yet allows for considerable depth and complexity. Stipple Effect has a feature-rich scripting API that... -
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Kisekae UltraKiss
Kisekae UltraKiss is a full featured integrated development environmen
UltraKiss is a computer program that implements the Kisekae Set system, KiSS, a Japanese graphics system originally developed to facilitate costume changes on virtual dolls. UltraKiss was developed to help artists build their KiSS sets. It is a full featured viewer for all KiSS dolls, games, and visual applications. It is also a complete graphical development environment for creating KiSS applications. It fully implements the FKiSS event driven programming language up to and including... -
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OWL Machine Learning
Machine learning algorithm using OWL
Feature construction and selection are two key factors in the field of Machine Learning (ML). Usually, these are very time-consuming and complex tasks because the features have to be manually crafted. The features are aggregated, combined or split to create features from raw data. This project makes use of ontologies to automatically generate features for the ML algorithms. -
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TinyDoodle
Simplistic sketching program for J2ME platform
TinyDoodle is a simplistic sketching program for J2ME (MIDP 2.0) mobile devices, geared for low resolution screen. Supported file format is Wireless Bitmap (WBMP). While it works best on touch-enabled devices with pointer dragging support, older devices with no pointer dragging or no touchscreen at all can also draw on it too. It is intended to be only a sketchpad; it can draw in black and white, with three pencil size selection, on a fixed canvas size. -
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AndroidAdapters
A library, which provides various Adapters for Android apps
"AndroidAdapters" is an Android-library, which provides feature-rich adapter implementations for providing the underlying data of widgets such as ListView, GridView, ExpandableListView and RecyclerView. -
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Easy Test Maker
A simple way to make multiple choice and written tests.
This program makes it easy to create tests by formatting them for you and compiling all the questions into one file. You have the option to include written questions, multiple choice questions, or both. Feel free to go back to previous questions and change them with the question select feature. When you are finished you can preview, print, or export your test and answer key. The format of the text is customizable by font, font size and line spacing. -
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Java Machine Learning Library is a library of machine learning algorithms and related datasets. Machine learning techniques include: clustering, classification, feature selection, regression, data pre-processing, ensemble learning, voting, ...
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FeatureSelection
Feature selection methods including correlation feature selection.
Small bundle of feature selection algorithms, most notably correlation feature selection (CFS by Mark A. Hall). Provides a light-weight interface and published under BSD license. -
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GA/SVM_BMC
GA/SVM for feature selection in microarraydata
GA/SVM for feature selection in microarraydata -
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Monopoly clone written in Java for 2-8 players (including computer players) that was designed to make quite a lot of things customisable from the user's point of view. Four board files are included. Two are based on regional variations of Monopoly but with places named after colours instead, the other two are there more to demonstrate what can be done. Hopefully there are no major bugs in the game - I cannot guarantee that there are none, but I've done some testing on Linux and Windows...
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Anumaan
Open source predictive text entry system from CDAC, Mumbai
Anumaan is a predictive text entry system developed by CDAC, Mumbai, India. It gives context sensitive text prediction. Hence, it helps in effective text entry. It is intended for people suffering from different kinds of motor disabilities. New version of standalone flavor of Anumaan (Anumaan-standalone-0.2) has been released. Feedback, feature enhancement requests about the application can be sent to ossd[at]cdac[dot]in or predictanumaan[at]gmail[dot]com. -
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...Il permet de jouer un son de son choix et d'afficher des alertes soit à une heure déterminée soit à la fin d'un compte à rebours. Just Wake Up is an alarm clock that allows to play music. It adds the special feature of wake up music selection.
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DimReduction project provide an open-source multiplatform (Java) graphical environment for bioinformatics problems that supports many feature selection algorithms, pattern recognition techniques, criterion functions and graphic visualization tools.
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Java GUI to analyze one (or more, in batch mode) datasets with several feature selection methods at the same time and also performing an "ensemble" analysis. It can be easily extended to include any feature selection algorithm.
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Case Based Reasoning is a technology to make a similarity based selection from a predefined set of cases. Each case is defined by a set of features. After some cases are stored it is possible to perform a search by specifying search feature values.
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Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.
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