CISCO 300-810 Implementing Cisco Collaboration Applications (CLICA) 06 25Oct2024 - Practice Quiz

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Question 1 of 30

In a machine learning project aimed at predicting customer churn for a telecommunications company, you are tasked with selecting the most appropriate algorithm to handle a dataset with a significant class imbalance (e.g., 90% non-churners and 10% churners). Given the need for high precision in predicting churners to minimize false positives, which algorithm would be most suitable for this scenario, considering the potential for overfitting and the need for interpretability?

Logistic Regression with class weights adjusted

Random Forest with default parameters

Support Vector Machine with a linear kernel

K-Nearest Neighbors with k=5

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