adplus-dvertising
frame-decoration

Question

How can the challenge associated with the k-means algorithm be mitigated?

a.

By increasing the number of clusters (k)

b.

By reducing the dimensionality of the data

c.

By running the algorithm multiple times with different initializations

d.

By using hierarchical clustering instead

Posted under Big Data Computing

Answer: (c).By running the algorithm multiple times with different initializations Explanation:To mitigate the challenge of sensitivity to initial centroid placements, it is common to run the k-means algorithm multiple times with different seeds and choose the results with the least total squared distance.

Engage with the Community - Add Your Comment

Confused About the Answer? Ask for Details Here.

Know the Explanation? Add it Here.

Q. How can the challenge associated with the k-means algorithm be mitigated?

Similar Questions

Discover Related MCQs

Q. Which category of clustering algorithms creates a nested set of clusters?

Q. What is the primary difference between agglomerative and divisive hierarchical clustering?

Q. In logistic regression, what is the dependent variable typically referred to as?

Q. What does the conditional probability of a category given the input represent in logistic regression?

Q. How is logistic regression different from linear regression?

Q. What type of table shows correct and incorrect classifications in logistic regression?

Q. What is the primary focus of reinforcement learning in machine learning?

Q. Which area of study in a control system deals with understanding the effect of inputs on the output?

Q. What is one of the challenges presented by dynamic systems in control theory?

Q. What does Gaussian processes offer as a family of stochastic processes in modeling dynamics?

Q. In the context of active learning, what does "exploitation" refer to?

Q. What is one of the design choices involved in modeling dynamic systems for learning and optimization?

Q. What does the Bayesian optimal control framework facilitate when modeling dynamic systems?

Q. Which machine learning approach is suitable for learning feedback operators in dynamic systems?

Q. What is the primary goal of feature construction in machine learning?

Q. What is a key challenge that smart cities aim to address using interconnected information?

Q. How can optimization algorithms help in smart city applications, such as water management?

Q. What is the main advantage of smarter traffic systems in urban areas?

Q. What is the primary focus of customer analytics in CRM BPO?

Q. What is one of the main challenges addressed in customer analytics?