Abstract: This research article identifies the fault occurrence in the blowfish cryptography algorithm using a modified Decision Tree classifier. Though there are several cryptography algorithms, the ...

Rapid diagnosis of bacterial pneumonia is crucial for clinical diagnosis and treatment, but traditional methods are time-consuming. The wide application of machine learning techniques in medical ...

Computer vision systems combined with machine learning techniques have demonstrated success as alternatives to empirical methods for classification and selection. This study aimed to classify tomatoes ...

AIFAD stands for Automated Induction of Functions over Algebraic Data Types and is an application written in OCaml that improves decision tree learning by supporting significantly more complex kinds ...

The complexity of heterologous protein production necessitates the careful selection of inducer concentrations and growth conditions for each protein and organism, posing a multidimensional ...

ABSTRACT: 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 ...

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, ...

Kenny Rogers’ description of a gambler, knowing what to throw away, knowing what to keep, could well apply to U.S. Navy data. “As you’re producing a large vast amount of data, it’s about the ability ...

Abstract: This paper presents a survey of evolutionary algorithms that are designed for decision-tree induction. In this context, most of the paper focuses on approaches that evolve decision trees as ...

The actual 5-year survival rates for Gynecological Endometrioid Adenocarcinoma with Squamous Differentiation (GE-ASqD) are rarely reported. The purpose of this study was to evaluate how histological ...