Generating Random Matrix with CatBoost Random Forest Classifier

This function utilizes the CatBoost library's random forest classifier to generate a random matrix, with labels assigned randomly.

Technology Stack : CatBoost, NumPy

Code Type : Python Function

Code Difficulty : Intermediate

                
                    
import catboost as cb
import numpy as np

def generate_random_matrix(rows, cols):
    # This function generates a random matrix using CatBoost's Random Forest
    model = cb.CatBoostClassifier()
    data = np.random.rand(rows, cols)
    labels = np.random.randint(2, size=rows)
    model.fit(data, labels)
    return model