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LIBLINEAR理论与源码解读(已完结)
A Perl binding for LIBLINEAR, a library for classification/regression using linear SVM and logistic regression.
Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence
Rust language bindings for the LIBLINEAR C/C++ library
Wrapper on top of liblinear-tools
An implementation of the NBSVM classifier for Weka
Rumale::SVM provides support vector machine algorithms of LIBSVM and LIBLINEAR with Rumale interface
Solved tasks of "Machine Learning" course, contains implementations of main machine learning algorithms.
.NET wrapper for LIBLINEAR written in C#
Grade: 15.2/20
A single file C++ header-only wrapper for LIBLINEAR library
Support Vector Machine classification with Spark, using LIBLINEAR and MLlib
A spam detector using Linear Regression Model machine learning algorithm, using Java, ElasticSearch, LIblinear, Weka, SparseFormat, ARFF format, Linear Regression,
This is same problem which is solved in https://github.com/ashishyadav24092000/Detect_Parkinson_XGBOOSTCLASSIFIER project. But here we have used Logistic Regression instead of XGBClassifier to classify the Statuses as 0 or 1 i.e. Parkinson positive or negative. And clearly we can see that how our Accuracy suddenly dropped from 95% to 84% as we moved from XGBClassifier to Logistic Regression.
Conan package for liblinear project
Liblinear-Ruby is Ruby interface of LIBLINEAR using SWIG. Now, this interface is supporting LIBLINEAR 2.30.
Numo::Liblinear is a Ruby gem binding to the LIBLINEAR