MATLAB Machine Learning

Abstract

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Aprendizaje Automático en Aplicaciones Fisioterapéuticas

“…La predicción o respuesta a datos futuros a partir de datos que realiza el AA ha sido usada comúnmente en ciencias sociales, en investigación de operaciones y en ciencias aplicadas (Cleophas and Zwinderman, 2013). Sin embargo, está área se ha vuelto muy importante en otras disciplinas como la ingeniería de vehículos autónomos, las finanzas para predecir el comportamiento del mercado, la ciberseguridad y en la medicina, se ha empleado para diagnóstico (Paluszek and Thomas, 2016).…”

Big Data: Myths, Realities and Perspectives - A Remote Look

“…Stocking, controlling, obtaining, and treating this large quantity of information constitute a vital requirement and a gigantic defy with a view to meet the expectation to discover, examine, extract, and envisage these data as information. This flood of data, in conjunction with rising methods and engineering employed to manage it, is frequently mentioned nowadays as Big Data computing [1,6]. Big Data may be described as bulks of data obtainable in changing levels of intricacy, produced at various rates and changing levels of confusion, that cannot be treated employing conventional engineering, treating techniques, algorithms, or any commercial off-the-shelf solutions [7,8].…”

Machine Learning: A Novel Approach to Predicting Slope Instabilities

“…Corrections are made to the model for the training process till the desired results are achieved. Classification and regression are examples of supervised learning [13]. (ii) Unsupervised learning: a set of data with unknown solution is used as the input data.…”

“…(ii) Unsupervised learning: a set of data with unknown solution is used as the input data. For unsupervised learning, a model is built by assuming the presence of structures in the input data by looking for redundancy or similarity in the data [13]. (iii) Semisupervised learning: dataset is a mixture of known and unknown solutions.…”

“…(iii) Semisupervised learning: dataset is a mixture of known and unknown solutions. For this learning, the model is built to understand structure and make predictions [13].…”