23 packages tagged with “ikvm”
Stanford CoreNLP provides a set of natural language analysis tools which can take raw English language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, and mark up the structure of sentences in terms of phrases and word dependencies, and indicate which noun phrases refer to the same entities. Stanford CoreNLP is an integrated framework, which make it very easy to apply a bunch of language analysis tools to a piece of text. Starting from plain text, you can run all the tools on it with just two lines of code. Its analyses provide the foundational building blocks for higher-level and domain-specific text understanding applications.
Curator client library & recipes for Zookeeper. This is the IKVM version; which is to say that this is compiled from Java to .NET
Stanford NER (also known as CRFClassifier) is a Java implementation of a Named Entity Recognizer. Named Entity Recognition (NER) labels sequences of words in a text which are the names of things, such as person and company names, or gene and protein names. The software provides a general (arbitrary order) implementation of linear chain Conditional Random Field (CRF) sequence models, coupled with well-engineered feature extractors for Named Entity Recognition.
Apache FOP, converted to .NET using IKVM
A Part-Of-Speech Tagger (POS Tagger) is a piece of software that reads text in some language and assigns parts of speech to each word (and other token), such as noun, verb, adjective, etc., although generally computational applications use more fine-grained POS tags like 'noun-plural'.
The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution. These tasks are usually required to build more advanced text processing services. OpenNLP also included maximum entropy and perceptron based machine learning.
An easy and quick way to use libsvm in your .NET projects. Envoy !
A natural language parser is a program that works out the grammatical structure of sentences, for instance, which groups of words go together (as \"phrases\") and which words are the subject or object of a verb. Probabilistic parsers use knowledge of language gained from hand-parsed sentences to try to produce the most likely analysis of new sentences.
Tokenization of raw text is a standard pre-processing step for many NLP tasks. For English, tokenization usually involves punctuation splitting and separation of some affixes like possessives. Other languages require more extensive token pre-processing, which is usually called segmentation.
F# extensions for Stanford.NLP.Parser
Apache OpenNLP for .NET via IKVM.
Use Java libraries from .NET with maven versioning
IBM MQ standalone client for .NET (converted official java client v9.0 via IKVM)
Sample how to use: https://gist.github.com/hodzanassredin/6682771 LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized classifiers L2-loss linear SVM, L1-loss linear SVM, and logistic regression (LR) L1-regularized classifiers (after version 1.4) L2-loss linear SVM and logistic regression (LR) L2-regularized support vector regression (after version 1.9) L2-loss linear SVR and L1-loss linear SVR. 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, Python, Ruby interfaces
Implementation of the Scala standard library in F#.
ADO.NET for H2 DB and serve IKVM
Nhibernate H2 driver compatible with .NET 5.0 by using IKVM
Advanced Java big math functions implementation using .NET Framework.
H2 Database Engine 1.4.200 compiled for .NET 8 using IKVM 8.14.0. Provides the embedded H2 JDBC driver ported to .NET.
.NET 5.0 conversion (using IKVM.NET) of the H2 SQL database library.
H2 Database Engine 1.4.200 compiled for .NET 8 using IKVM 8.14.0
H2 Database Engine 2.4.240 compiled for .NET 8 using IKVM 8.14.0. Provides the embedded H2 JDBC driver ported to .NET.
H2 Database Engine 2.2.222 compiled for .NET 8 using IKVM 8.14.0. Provides the embedded H2 JDBC driver ported to .NET.