Here's what that shift to AI means for the recruitment process, and how you can ensure your application gets picked from the ...
In order to improve the accuracy and efficiency of sports training data analysis, this paper proposes an optimized analysis model by combining Iterative Dichotomiser 3 (ID3) decision tree algorithm ...
Inductive Learning Algorithm (ILA) is an iterative and inductive machine learning algorithm that is used for generating a set of classification rules, which produces rules of the form “IF-THEN”, for a ...
Decision tree is an effective supervised learning method for solving classification and regression problems. This article combines the Pearson correlation coefficient with the CART decision tree, ...
Abstract: In mining data streams the most popular tool is the Hoeffding tree algorithm. It uses the Hoeffding's bound to determine the smallest number of examples needed at a node to select a ...
Abstract: This paper describes a new algorithm for obtaining rules automatically from training examples. The algorithm is applicable to examples involving both objects: with discrete and ...
A k-nearest neighbors is algorithm used for classification and regression. It classifies a new data point by finding the k-nearest points in the training dataset and assigns it the majority class ...
Machine learning (ML) approaches are a collection of algorithms that attempt to extract patterns from data and to associate such patterns with discrete classes of samples in the data—e.g., given a ...
ABSTRACT: The information gained after the data analysis is vital to implement its outcomes to optimize processes and systems for more straightforward problem-solving. Therefore, the first step of ...
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