sklearn (scikit-learn)

This function uses the Random Forest algorithm for classification, accepts the dataset and labels as input, and returns a classification report.

Machine learning classification 2024-12-16 11:57:32 3 views

Scikit-learn NumPy

This function trains a Support Vector Machine (SVM) classifier using Scikit-learn and returns a classification report.

The type of code 2024-12-16 11:51:48 3 views

Scikit-learn Numpy

This function uses the Scikit-learn library's SVC (Support Vector Classifier) to train and evaluate a classification model. It first splits the dataset into training and test sets, then scales the features, creates an SVC model with a linear kernel, trains the model, makes predictions on the test set, and finally returns the classification report.

Machine learning classifier 2024-12-16 11:47:55 7 views

Scikit-learn train_test_split

The code uses Scikit-learn's `train_test_split` for dataset splitting, `StandardScaler` for feature standardization, `SVC` for the Support Vector Classifier with a radial basis function (RBF) kernel, and `classification_report` for evaluation.

The type of code 2024-12-16 11:41:11 3 views

Scikit-learn NumPy

This function first generates a random classification dataset, then trains and predicts using a Random Forest classifier, and finally returns a classification report.

Machine learning classification 2024-12-16 11:37:57 3 views

scikit-learn numpy

This function uses a random forest classifier for classification. It first splits the dataset into training and testing sets, then standardizes the features, trains a random forest model, predicts on the test set, and finally returns a classification report.

Function 2024-12-07 16:29:04 6 views

scikit-learn

This function uses a Random Forest classifier to classify the Iris dataset and outputs a classification report.

Machine learning 2024-12-07 16:21:42 3 views

The code

This code defines a function that uses a random forest classifier to classify the given dataset and generates a classification report.

Function 2024-12-07 15:56:49 4 views

Scikit-learn

This function uses a random forest classifier to classify the given features and labels, and prints out a classification report. First, the data set is split into training and testing sets using the train_test_split function. Then, a random forest classifier is initialized and trained on the training set. Finally, predictions are made on the test set, and a classification report is printed.

Machine learning 2024-11-30 15:55:23 4 views