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About: Divvy is a Mac OS X application for performing dimensionality reduction, clustering, and visualization. Changes:Initial Announcement on mloss.org.
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About: Epistatic miniarray profiles (E-MAPs) are a high-throughput approach capable of quantifying aggravating or alleviating genetic interactions between gene pairs. The datasets resulting from E-MAP experiments typically take the form of a symmetric pairwise matrix of interaction scores. These datasets have a significant number of missing values - up to 35% - that can reduce the effectiveness of some data analysis techniques and prevent the use of others. This project contains nearest neighbor based tools for the imputation and prediction of these missing values. The code is implemented in Python and uses a nearest neighbor based approach. Two variants are used - a simple weighted nearest neighbors, and a local least squares based regression. Changes:Initial Announcement on mloss.org.
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About: CN24 is a complete semantic segmentation framework using fully convolutional networks. Changes:Initial Announcement on mloss.org.
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About: Gaussian processes with general nonlinear likelihoods using the unscented transform or Taylor series linearisation. Changes:Initial Announcement on mloss.org.
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About: Estimates statistical significance of association between variables and their principal components (PCs). Changes:Initial Announcement on mloss.org.
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About: DDN learns and visualize differential dependency networks from condition-specific data. Changes:Initial Announcement on mloss.org.
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About: A toolkit for hyperparameter optimization for machine learning algorithms. Changes:Initial Announcement on mloss.org.
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About: ruptures is a Python library for off-line change point detection. This package provides methods for the analysis and segmentation of non-stationary signals. Implemented algorithms include exact and approximate detection for various parametric and non-parametric models. ruptures focuses on ease of use by providing a well-documented and consistent interface. In addition, thanks to its modular structure, different algorithms and models can be connected and extended within this package. Changes:Initial Announcement on mloss.org.
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About: Learns dynamic network changes across conditions and visualize the results in Cytoscape. Changes:Initial Announcement on mloss.org.
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About: Baycomp is a library for Bayesian comparison of classifiers, as a better alternative for null-hypothesis significance testing. Changes:Initial Announcement on mloss.org.
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About: Kaiye Wang, Ran He, Wei Wang, Liang Wang, Tiuniu Tan. Learning Coupled Feature Spaces for Cross-modal Matching. In ICCV, 2013. Changes:Initial Announcement on mloss.org.
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About: The Chestnut Machine Learning Library is a suite of machine learning algorithms written in Python with some code written in C for efficiency. Most algorithms are called with a simple, functional API [...] Changes:Initial Announcement on mloss.org.
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About: An open-source C# market-basket synthetic data generator, capable of creating transactions, sequences and taxonomies, based on the IBM Quest version. Written to address the maintainability and portability problems of the original, feedback, fixes and extensions are encouraged! Changes:Initial Announcement on mloss.org.
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About: A descriptive and programming language independent format and API for the simplified configuration, documentation, and design of computer experiments. Changes:Initial Announcement on mloss.org.
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About: MLlib provides a distributed machine learning (ML) library to address the growing need for scalable ML. MLlib is developed in Spark (http://spark.incubator.apache.org/), a cluster computing system designed for iterative computation. Moreover, it is a component of a larger system called MLbase (www.mlbase.org) that aims to provide user-friendly distributed ML functionality both for ML researchers and domain experts. MLlib currently consists of scalable implementations of algorithms for classification, regression, collaborative filtering and clustering. Changes:Initial Announcement on mloss.org.
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About: Motivated by a need to classify high-dimensional, heterogeneous data from the bioinformatics domain, we developed ML-Flex, a machine-learning toolbox that enables users to perform two-class and multi-class classification analyses in a systematic yet flexible manner. ML-Flex was written in Java but is capable of interfacing with third-party packages written in other programming languages. It can handle multiple input-data formats and supports a variety of customizations. MLFlex provides implementations of various validation strategies, which can be executed in parallel across multiple computing cores, processors, and nodes. Additionally, ML-Flex supports aggregating evidence across multiple algorithms and data sets via ensemble learning. (See http://jmlr.csail.mit.edu/papers/volume13/piccolo12a/piccolo12a.pdf.) Changes:Initial Announcement on mloss.org.
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About: Distributed optimization: Support Vector Machines and LASSO regression on distributed data Changes:Initial Upload
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About: Piqle (Platform for Implementing Q-Learning Experiments) is a Java framework for fast design, prototyping and test of reinforcement learning experiments (RL). By clearly separating algorithms and problems, it allows users to focus on either part of the RL paradigm:designing new algorithms or implementing new problems. Piqle implements many classical RL algorithms, making their parameters easily tunable. At this time, 13 problems are implemented, several with one or more variants. The user's manual explains in detail how to code a new problem. Written in Java, Piqle is as platform-independent as Java itself. Its components can easily be embedded as part of complex implementations, like robotics or decision making. Changes:Initial Announcement on mloss.org.
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About: ARTOS can be used to quickly learn models for visual object detection without having to collect a set of samples manually. To make this possible, it uses ImageNet, a large image database with more than 20,000 categories. Changes:Initial Announcement on mloss.org.
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About: A MATLAB toolkit for performing generalized regression with equality/inequality constraints on the function value/gradient. Changes:Initial Announcement on mloss.org.
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