Can running injuries be predicted using only a dataset and machine learning models? This paper explores this question classification models, including the Logistic Regression model Random Forest Classifier model. In used, ten features were taken into account when predicting injuries. With slight modifications, Weighted over down-sampling models used to mitigate imbalance in dataset. The results...

Legal classification models help lawyers identify the relevant documents required for a study. In this study, focus is on sentence level classification. To be more precise, work undertaken focuses conversation in supreme court between justice and other correspondents. both naïve Bayes classifier logistic regression are used to classify conversations at level. The performance measured with of ar...

In recent years, Web services are becoming more and intelligent (e.g., in understanding user preferences) thanks to the integration of components that rely on Machine Learning (ML). Before users can interact (inference phase) with an ML-based service (ML-Service), underlying ML model must learn (training from existing data, a process requires long-lasting batch computations. The management thes...

Machine learning models fit complex algorithms to arbitrarily large datasets. These are well known be high on performance and low interpretability. We use interactive visualization of slices predictor space address the interpretability deficit; in effect opening up black-box machine algorithms, for purpose interrogating, explaining, validating comparing model fits. Slices specified directly thr...

Introduction: This article is the result of research entitled "Development a prototype to optimize access conditions SENA-Pescadero using artificial intelligence and open-source tools", developed at Servicio Nacional de Aprendizaje in 2020. Problem: How identify Machine Learning Techniques applied computer vision processes through literature review? Objective: Determine application, as well adv...