The R package iRF implements iterative Random Forests, a method for iteratively growing ensemble of weighted decision trees, and detecting high-order feature interactions by analyzing feature usage on ...
weightederm is a scikit-learn-style package for fast and accurate offline change point detection and estimation (or data segmentation) in regression settings via weighted empirical risk minimization ...
Abstract: A random marker code is inserted into the information sequences periodically, and a novel symbol-level decoding algorithm considering the weighted Levenshtein distance (WLD) is designed for ...
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Abstract: Joint Timing and Channel Estimation (JTCE) for bandlimited long-code-aided Multi-Carrier Direct-Sequence Code Division Multiple Access (MC-DS-CDMA) systems is investigated. We establish the ...
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In the first phase, stroke activations with baseline NCCT and CT angiography were used to train an aICV‐NCCT. The algorithm was then internally validated using intraclass correlations and Intersection ...
The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict the price of a particular make and model of a used car based on its ...
In response to the shortcomings of the Salp Swarm Algorithm (SSA) such as low convergence accuracy and slow convergence speed, a Multi-Strategy-Driven Salp Swarm Algorithm (MSD-SSA) was proposed.
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