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 ...
Reproducible experiments and testimony presented at a recent webinar suggest LinkedIn’s algorithms systematically reduce the visibility of anyone whose profile doesn't match the patterns the algorithm ...
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 ...
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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