Category Machine learning

Decision trees Decision trees

The tree and the labyrinth

A decision tree is a machine learning model that is used to estimate a target variable based on several input variables. This target variable can be either numerical (regression trees) or nominal (classification trees). The methodology for constructing decision trees for regression and classification is described, as well as their interpretation.

F1-score

An intruder from another world

The F1-score, also called F-score or F-measure, is an estimator of the classification capacity of a test that is frequently used in data science and artificial intelligence algorithms and that can be useful for evaluation of diagnostic tests. It is the harmonic mean of sensitivity and positive predictive value, so it weights the value of both in a single estimator.

Decision trees Decision trees

The intelligent decalogue

The aspects that must be assessed for the critical appraisal of documents that use machine learning techniques are reviewed, including the selection of participants, the treatment of the data during the development of the model and its final implementation in clinical practice.

Decision trees Decision trees

Science behind the magic

A neural network consists of a series of layers of processing units, called neurons, that perform transformations on input data to generate output data. The fundamentals of the internal functioning of an artificial neural network are described.

Decision trees Decision trees

Hasta la vista, baby

Artificial intelligence is the simulation of human intelligence in machines programmed to think and learn like humans so that they can automate tasks that are normally performed by humans. Machine learning develops and applies models and algorithms that are capable of learning from data.

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