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- Mahout currently has Collaborative Filtering User and Item based recommenders K-Means, Fuzzy K-Means clustering Mean Shift clustering...Mahout currently has Collaborative Filtering User and Item based recommenders K-Means, Fuzzy K-Means clustering Mean Shift clustering Dirichlet process clustering Latent Dirichlet Allocation Singular value decomposition Parallel Frequent Pattern mining Complementary Naive Bayes classifier Random forest decision tree based classifier High performance java collections (previously colt collections) A vibrant community and many more cool stuff to come by this summer thanks to Google summer of code
- The Knowledge Discovery Machine Learning (KDML) group focuses on the neighboring subfields of computer science known as knowledge discovery in databases (K...The Knowledge Discovery Machine Learning (KDML) group focuses on the neighboring subfields of computer science known as knowledge discovery in databases (KDD, sometimes referred to simply as data mining) and machine learning (ML). For us, these fields include on the one hand the automated analysis of large data sets using intelligent algorithms that are capable of extracting from the collected data hidden knowledge in order to produce models that can be used for prediction and decision making. On the other hand, they also include algorithms and systems that are capable of learning from experience and adapting to their environment or their users.
- Data Mining, Analytics, and Databases Databases are the workhorse of the enterprise today. Searching through databases and finding useful informat...Data Mining, Analytics, and Databases Databases are the workhorse of the enterprise today. Searching through databases and finding useful information has become a big computational challenge. Researchers from academia and Microsoft, Oracle, SAP, and many other corporations are looking to CUDA-enabled GPUs to find a scalable solution.
- LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM,...LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM. Main features of LIBLINEAR include * Same data format as LIBSVM, our general-purpose SVM solver, and also similar usage * Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer * Cross validation for model selection * Probability estimates (logistic regression only) * Weights for unbalanced data * MATLAB/Octave, Java interfaces
- Social Spam Detection
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