Pearson Correlation Coefficient

2020

Citations in the corpus

Measuring Data (2022, methodology): “There are many choices for measuring correlations: some of the most commonly used measurements are the Pearson correlation coefficient (Benesty et al., 2009) and the Spearman rank-order correlation coefficient (Ramsey, 1989; Kokoska and Zwillinger, 2000), which can help represent inter-dataset relat”
FIRM: An Intelligent Fine-Grained Resource Management Framework for SLO-Oriented Microservices (2020, methodology): “To do so, we use the Pearson correlation coefficient [12] (also called zero-order correlation), i.”
Poly Kernel Inception Network for Remote Sensing Detection (2024, methodology): “To measure the model’s detection sensitivity concerning the sizes of different categories, we utilize Pearson Correlation Coefficient (PCC) [5] to quantify the linear correlation be-tween the average bounding box area per category and the average detection score per category of DOTA-v1.”
An Overview of Voice Conversion and Its Challenges: From Statistical Modeling to Deep Learning (2020, background): “The common objective evaluation metrics include Mel-cepstral distortion (MCD) [246] for spectrum, and PCC [247] and RMSE [248]–[250] for prosody.”
Discovering biomarkers associated and predicting cardiovascular disease with high accuracy using a novel nexus of machine learning techniques for precision medicine (2023, methodology): “The proposed feature selection model uses four distinct algorithms: (I) Recursive Feature Elimination (RFE) 24 , (II) Pearson Correlation 25 , (III) Chi-Square Test 26 , and IV) Analysis of Variance (ANOVA) 27 .”
A Reinforcement Learning Framework for Explainable Recommendation (2018, methodology): “To this end, we design a consistency measure based on the Pearson correlation [23]:”
Speech Representation Disentanglement with Adversarial Mutual Information Learning for One-shot Voice Conversion (2022, methodology): “To evaluate intonation variations of the converted voice, PCC between F0 of source and converted voice is calculated.”
SourceFinder: Finding Malware Source-Code from Publicly Available Repositories (2020, methodology): “We use a common correlation metric, the Pearson Correlation Coefficient (r) [6], measured in a scale of [−1,1].”