ABSTRACT: Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches ...

This study aims to establish an interpretable disease classification model via machine learning and identify key features related to the disease to assist clinical disease diagnosis based on a ...

Are self-driving vehicles really just big, remote-controlled cars, with nameless and faceless people in far-off call centers piloting the things from behind consoles? As the vehicles and their science ...

Abstract: Performance evaluation of the linear kernel SVM for land cover classification using the GEE platform in Telangana, India (Longitude: 79.78E Latitude: 7.78N) is presented in this paper.

Common Kernel Types in SVC Kernel Name kernel= Use Case Notes Linear 'linear' When data is linearly separable Fastest and most interpretable Polynomial 'poly' For curved boundaries Can capture more ...

ABSTRACT: Industrial appearance anomaly detection (AD) focuses on accurately identifying and locating abnormal regions in images. However, due to issues such as scarce abnormal samples, complex ...

This project classifies text messages as either spam or ham (not spam) for feature extraction and Support Vector Machines (SVM) for classification. Python: The programming language used for model ...

Linear and kernel methods are important machine learning techniques for data classification. Popular examples include support vector machines (SVM) and logistic regression. We begin with an ...