Evidence Based Medicine pills
Evidence Based Medicine pills
Simple decision trees have the problem of being less accurate than other regression or classification algorithms, as well as being less robust to small modifications of the data with which they are built. Some techniques for building ensemble decision trees are described, such as resampling aggregation (bagging) and random forests, which aim to improve the accuracy of predictions and avoid overfitting of models.
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.
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.
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.
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.