We assessed the association of emergent classification of an ED visit based on the New York University ED Algorithm (EDA) with hospital mortality and hospital admission. Using diagnosis codes ...

The weighted k-NN classification algorithm has received increased attention recently for two reasons. First, by using neural autoencoding, k-NN can deal with mixed numeric and non-numeric predictor ...

where n is the grand total of ED visits, c is the number of columns in a classification table, and r is the number of visit classes.The P value for the significance of V is the same as for Pearson ...

When using k-NN classification it's important to normalize ... and no closest neighbors are class 2. The k-NN classification algorithm is often effective, but it's rather primitive. The scikit library ...

Data processing software normally solves functional problems,since input data is processed according to an algorithm (i.e. thefunction ... The first step in using the classification tree method is ...

The job of classification is sometimes the ultimate goal of an algorithm. Many data scientists use AI algorithms to preprocess their data and assign categories. Simply observing the world and ...