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KNIME allows users to visually create data flows (or pipelines), selectively execute some or all analysis steps, and later inspect the results, models, using interactive widgets and views. KNIME is written in Java and based on Eclipse. It makes use of an extension mechanism to add plugins providing additional functionality.
In computing, a pipeline or data pipeline [1] is a set of data processing elements connected in series, where the output of one element is the input of the next one. The elements of a pipeline are often executed in parallel or in time-sliced fashion. Some amount of buffer storage is often inserted between elements. Computer-related pipelines ...
Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...
In computer engineering, instruction pipelining is a technique for implementing instruction-level parallelism within a single processor. Pipelining attempts to keep every part of the processor busy with some instruction by dividing incoming instructions into a series of sequential steps (the eponymous "pipeline") performed by different processor units with different parts of instructions ...
Spark NLP for Healthcare is a commercial extension of Spark NLP for clinical and biomedical text mining. [10] It provides healthcare-specific annotators, pipelines, models, and embeddings for clinical entity recognition, clinical entity linking, entity normalization, assertion status detection, de-identification, relation extraction, and spell checking and correction.
This lets businesses forgo preload transformations and replicate raw data into their data warehouses, where it can transform them as needed using SQL. After having used ELT, data may be processed further and stored in a data mart. [13] Most data integration tools skew towards ETL, while ELT is popular in database and data warehouse appliances.
The name "pipeline" comes from a rough analogy with physical plumbing in that a pipeline usually [2] allows information to flow in only one direction, like water often flows in a pipe. Pipes and filters can be viewed as a form of functional programming , using byte streams as data objects.
CellProfiler 4.0 was released in September 2020 and focused on speed, usability, and utility improvements with most notable example of migration to Python 3. [ 17 ] Community