Lebron

<p>This dataset opens the door to the intricacies of the 2023 NBA season, offering a profound understanding of the art of scoring in professional basketball.</p>

datasets

Automatically returns 36 logistic models including 23 individual models and 13 ensembles of models of logistic data. The package also returns 10 plots, 5 tables, and a summary report. The package automatically
builds all 36 models, reports all results, and provides graphics to show how the models performed. This can be used for a wide range of data sets. The package includes medical data (the Pima Indians data set), and
information about the performance of Lebron James. The package can be used to analyze many other examples, such as stock market data. The package automatically returns many values for each model, such as
True Positive Rate, True Negative Rate, False Positive Rate, False Negative Rate, Positive Predictive Value, Negative Predictive Value, F1 Score, Area Under the Curve. The package also returns 36 Receiver
Operating Characteristic (ROC) curves for each of the 36 models.

Russ Conte

LogisticEnsembles

Automatically Runs 36 Logistic Models (Individual and Ensembles)

Lebron function

<p>An object of class <code>data.frame</code> with 1533 rows and 12 columns.</p>

Lebron: Lebron—A logistic data set, with the result indicating whether or not Lebron scored on each shot in the data set.

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