Libraries and Development Kits for Data Mining

• AC2 (from Isoft), a set of librairies for building data mining solutions on the server side.
• Clementine Solution Publisher generates embedded SQL and C code for processing and modeling steps performed in Clementine.
• Data Intelligence Add-In for Excel, integrates the most popular algorithms found in data mining and AI into Excel.
• Decision Science SDK, from Stone Analytics enables developers to embed predictive models in their applications.
• GEPSR, a COM component for integrating Gene Expression Programming into custom applications.
• KnowledgeSTUDIO SDK, offering enterprise application developers access to an extensive API and library of data mining components
• KXEN Components, based on Vapnik Support Vector Machines theory.
• K.wiz, open Java data mining and knowledge discovery platform providing a full API and extensive range of data mining components.
  K.wiz Application Enterprise enables building packaged analytical applications using HTML, XML and Javascript.
• The LPA Data Mining Toolkit provides an embeddable collection of routines which support the discovery of association rules within RDMS.
• Microsoft OLE DB for Data Mining, SQL Server 2005 Books Online.
• MLF: machine learning framework for Mathematica, the multi-method system for creating understandable computational models from data
• NAG Data Mining Components, statistics and machine learning components for data cleaning, transformation and model building -- for creating applications with data mining functionality.
• Neusciences aXi.DecisionTree and aXi.Kohonen, ActiveX Controls for building a decision tree and Kohonen Clustering. Includes a Delphi interface.
• PolyAnalyst COM, an SDK offering a large selection of machine learning algorithms as separate COM components for simple integration in external applications.
• TextAnalyst COM, an SDK for building intelligent applications with semantic analysis, summarization, clustering, categorization, and retrieval of texts and fragments.
• Waffles, an open source library of machine learning and data mining tools in C++, includes several classifiers, clustering algorithms, dimensionality reduction algorithms, and much more.
• WizWhy-OCX, ActiveX control includes all the functions of WizWhy rule-finding product
• XAffinity(tm), ActiveX toolkit (DLL) for association and sequential analysis in SQL databases.
• XELOPES, an open platform-independent and data-source-independent library for Embedded Data Mining.

• Data Mining Template Library (DMTL), an open-source collection of generic algorithms and data structures for mining complex patterns, including Itemsets, Sequences, Trees and graphs.
• Orange, C++ components for data mining,includes preprocessing, modelling and data exploration techniques.
• Sav Z, Java(TM) API language for developing high-performance mobile object-relational database applications (an improved JDBC). Free download!
• VFML (Very Fast Machine Learning) library for mining very large databases and data streams. Written in C, it includes highly scalable implementations of several widely used machine learning algorithms and tools for data preparation, testing, and rapid development of stream mining systems.
• Weka, collection of machine learning algorithms for solving real-world data mining problems (in Java).
• XML Miner, offers a class library for mining data and text expressed in XML, extracting knowledge and re-using that knowledge in products and applications in the form of fuzzy logic expert system rules.