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Bubble sort, sometimes referred to as sinking sort, is a simple sorting algorithm that repeatedly steps through the input list element by element, comparing the current element with the one after it, swapping their values if needed.
If block A1 is accessed at time 1, its recency will be 0; this is the first-accessed block and the IRR will be 1, since it predicts that A1 will be accessed again in time 3. In time 2, since A4 is accessed, the recency will become 0 for A4 and 1 for A1; A4 is the most recently accessed object, and the IRR will become 4.
Bootstrap aggregating, also called bagging (from bootstrap aggregating) or bootstrapping, is a machine learning (ML) ensemble meta-algorithm designed to improve the stability and accuracy of ML classification and regression algorithms.
A 1-bit saturating counter (essentially a flip-flop) records the last outcome of the branch. This is the most simple version of dynamic branch predictor possible, although it is not very accurate. A 2-bit saturating counter [1] is a state machine with four states: Figure 2: State diagram of 2-bit saturating counter. Strongly not taken; Weakly ...
In computer science, a data buffer (or just buffer) is a region of memory used to store data temporarily while it is being moved from one place to another. Typically, the data is stored in a buffer as it is retrieved from an input device (such as a microphone) or just before it is sent to an output device (such as speakers); however, a buffer may be used when data is moved between processes ...
Relief is an algorithm developed by Kira and Rendell in 1992 that takes a filter-method approach to feature selection that is notably sensitive to feature interactions. [1] [2] It was originally designed for application to binary classification problems with discrete or numerical features.
Weak supervision (also known as semi-supervised learning) is a paradigm in machine learning, the relevance and notability of which increased with the advent of large language models due to large amount of data required to train them.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...