Search Results for "algorithm" - Page 2

We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community,...

This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces.

...It supports on-line prediction of new observations (no need to retrain); and supports datasets that contain both continuous (e.g. CPU load) and categorical (e.g. VM instance type) features. In particular, we use an unsupervised formulation of the Random Forest algorithm to calculate similarities and provide them as input to a clustering algorithm. For the sake of efficiency and meeting the dynamism requirement of autonomic clouds, our methodology consists of two steps: (i) off-line clustering and (ii) on-line prediction. RF+PAM can: Cluster observations (Unsupervised Learning) Calculate the dissimilarity between 2 or more observations (how different two observations are)

Locally Weighted Projection Regression (LWPR) is a fully incremental, online algorithm for non-linear function approximation in high dimensional spaces, capable of handling redundant and irrelevant input dimensions. At its core, it uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space. A locally weighted variant of Partial Least Squares (PLS) is employed for doing the dimensionality reduction.

Educational Learning Classifier System (eLCS) is a set of learning classifier system (LCS) educational demos designed to introduce students or researchers to the basics of a modern Michigan-style LCS algorithm. This eLCS package includes 5 different implementations of a basic LCS algorithm, as part of a 6 stage set of demos that will be paired with the first introductory LCS textbook. Each eLCS implementations (from demo 2 up to demo 6) progressively add major components of the entire LCS algorithm in order to illustrate how work, how they are coded, and what impact they have on how an LCS algorithm runs. ...

A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer Vision and Pattern Recognition, 2012. This source code is provided without warranty and is available under the GPL license. ...

TexLexAn is an open source text analyser for Linux, able to estimate the readability and reading time, to classify and summarize texts. It has some learning abilities and accepts html, doc, pdf, ppt, odt and txt documents. Written in C and Python.

...Play the first song from the Now Playing list, it'll recommend you next songs from the same list. NOTE: MAKE SURE THAT SONG SHUFFLE IS TURNED OFF WHILE USING PRONAC. Based upon K-Nearest Neighbor Machine Learning Algorithm, K-Fold Cross Validation and EchoNest for audio features.

...The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems. Each folder corresponds to a specific algorithm or concept, making it easy for learners to navigate and practice. The exercises serve as practical, hands-on reinforcement of theoretical concepts taught in the course. This collection is valuable for students and practitioners who want to strengthen their skills in machine learning through coding exercises.

a distributed engine for abstract neural network development via natural-language programming