XGBoost

This function uses an XGBoost model to predict the species of iris flowers based on given features and returns the predicted species labels.

Prediction function 2024-12-16 12:17:41 15 views

XGBoost NumPy

This function generates a random XGBoost model for classification or regression tasks. It takes a feature matrix X and a label vector y as input and returns a trained XGBoost model.

Custom function 2024-12-16 12:16:25 13 views

XGBoost NumPy

This function uses the XGBoost library to train a classification model and evaluates its accuracy on a test set.

Python Function 2024-12-16 12:15:38 15 views

XGBoost library

This function uses the XGBoost library to train a regression model and predict the results of the test dataset. It first loads the Boston housing dataset, then splits it into training and testing sets. Next, it creates an XGBoost regressor and uses the training set to train this model. Finally, it uses the trained model to predict the results of the test set.

The type of code 2024-12-16 12:15:24 19 views

XGBoost NumPy

This function trains an XGBoost model for classification or regression. It randomly selects model parameters and trains the model using random sample training data.

XGBoost model training function 2024-12-16 12:14:55 8 views

XGBoost scikit-learn

This function uses the XGBoost library to predict heart disease. It first loads the dataset, then splits it into training and testing sets. Next, it creates an XGBoost classifier and trains it on the training set. Finally, it uses the model to make predictions on the test set and calculates the accuracy.

Machine learning prediction function 2024-12-16 12:14:12 6 views

XGBoost Numpy

This function uses the XGBoost library to train a binary classifier. It accepts training data X_train and corresponding labels y_train, and returns the trained XGBoost classifier.

The type of code 2024-12-16 12:13:06 6 views

The code

This function defines a Python function using the XGBoost library to train a regression model and make predictions on new data. The function accepts training data, training labels, test data, and an optional number of rounds.

The type of code 2024-12-16 12:10:13 5 views

XGBoost NumPy

This function uses the XGBoost library to split the given dataset randomly, then trains an XGBoost classifier, and makes predictions on the test set.

The type of code 2024-12-16 12:10:08 3 views

XGBoost NumPy

This function randomly selects the most important features from the given dataset and returns their names and importance scores.

Function 2024-12-16 12:09:20 5 views