Igraph

The function performs a random walk on a given graph starting from a specified node for a given number of steps. At each step, it randomly selects the next node from the neighbors of the current node based on a weight.

Function 2024-12-16 12:00:13 14 views

NetworkX

This function performs a random walk on a given graph G starting from start_node, with num_steps specifying the number of steps in the walk. In each step, the function randomly selects a neighbor from the current node's neighbors as the next step.

Function 2024-12-16 11:56:45 4 views

Scikit-learn

This function uses the K-Nearest Neighbors (KNN) classifier from the Scikit-learn library to train and predict on the iris dataset. It first loads the iris dataset, then splits it into training and testing sets, creates a KNN classifier for training, and finally makes predictions on the test set.

Machine learning 2024-12-16 11:42:29 3 views

scikit-learn

This function uses the KNeighborsClassifier from the scikit-learn library to predict the species of flowers in the Iris dataset. It first loads the Iris dataset, then splits it into training and testing sets. A KNN classifier is created, trained on the training set, and then used to predict the labels on the test set.

Machine learning prediction function 2024-12-16 11:41:45 4 views

NetworkX for

This function performs a random walk on a graph G starting from the start_node for num_steps. At each step, the function chooses the next node based on the degree of the neighbors of the current node.

The type of code 2024-12-16 11:41:40 18 views

scikit-learn (sklearn.datasets

This function uses the K-Nearest Neighbors (KNN) algorithm to classify the iris dataset and calculate the accuracy on the test set.

Machine Learning Classification Algorithms 2024-12-16 11:38:29 4 views

Scikit-learn K-Nearest

This function uses the K-Nearest Neighbors (KNN) classifier from the Scikit-learn library to classify the iris dataset. It first loads the dataset, then splits it into training and testing sets. Next, it initializes the KNN classifier and trains it on the training data. Finally, it uses the trained model to predict the labels of the test set and returns the predictions.

Machine learning classification 2024-12-16 11:30:12 3 views

Igraph Random

This function generates a random walk on the given graph. It starts from a randomly chosen vertex and then follows the rule of randomly choosing neighbors, repeating this process for the specified number of steps.

The type of code 2024-12-16 11:23:31 3 views

scikit-learn

This function loads the Iris dataset and then trains and predicts using the K-Nearest Neighbors (KNN) algorithm. It accepts an argument arg1, which represents the number of neighbors used in the KNN model.

Machine learning prediction 2024-12-07 16:29:20 4 views

scikit-learn library's

This function uses the iris dataset from the scikit-learn library and the K-Nearest Neighbors algorithm to classify data, and returns the accuracy of the classification.

Function 2024-12-07 16:28:51 3 views