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- OutputCollector Description: An output receiver in the context of Hadoop is a fundamental interface used to collect and manage the data generated by a MapReduce(...) Read more
- Operator API Description: The Operator API in the context of big data frameworks is an application programming interface that defines how software components(...) Read more
- Output Schema Description: The 'Output Schema' in data processing frameworks refers to the structure that defines the format of the data generated as a result(...) Read more
- Operator overloading Description: Operator overloading is a feature of the C++ programming language that allows developers to redefine how operators work for(...) Read more
- Output Partitioning Description: Output partitioning in data processing frameworks refers to the process of dividing the data generated by an operation into(...) Read more
- Offline Processing Description: Offline processing refers to the manipulation and analysis of data that is not performed in real-time, allowing organizations to(...) Read more
- Operational Reporting Description: Operational Reports are documents that provide detailed information about the operational performance of a business. These reports(...) Read more
- On-Demand Streaming Description: On-demand streaming is a method of data transmission that allows users to access multimedia content, such as videos, music, or(...) Read more
- Ordered Stream Description: Ordered stream refers to a type of data streaming where it is ensured that data points are processed in the same order they were(...) Read more
- Output Rate Description: The output rate refers to the speed at which data is produced or sent from a system. This concept is fundamental in the field of(...) Read more
- Over-sampling Description: Oversampling is a technique used in the field of data science and statistics to increase the number of instances in the minority(...) Read more
- Outlier Removal Description: Outlier removal is the process of identifying and removing data points that significantly deviate from the rest of a dataset. These(...) Read more
- Overlapping Clusters Description: Overlapping clusters are a phenomenon in data analysis where two or more groups of data share some common points, complicating the(...) Read more
- Objective Function Description: The objective function is a fundamental component in the training of machine learning models, as it represents the metric that is(...) Read more
- Outlier Analysis Description: Outlier analysis refers to the examination of data points that significantly deviate from the expected behavior within a dataset.(...) Read more
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