17 Questions
What determines the clusters significantly when the number of data is not large?
Initial grouping
Which factor must be determined before carrying out k-mean clustering?
Number of clusters (K)
What is a disadvantage of k-mean clustering according to the text?
Resulting clusters depend on initial random assignments
Why might the algorithm of k-mean clustering be trapped in a local optimum?
Different initial conditions may produce different results
What indicates that the computation of k-mean clustering has reached stability?
No more iteration needed
Why does k-mean clustering not yield the same result with each run according to the text?
Random initialization
What may produce different cluster results if the same data is inputted in a different order?
K-means algorithm
Why is big data considered challenging in terms of volume?
Exponential increase in collected/generated data
What kind of data feed is mentioned as contributing to the increase in data volume?
Data feeds containing environmental, location, and other information
In what way does high-frequency stock trading impact the data landscape?
It reflects market changes within microseconds
Which type of devices generate massive log data in real-time according to the text?
Infrastructure and sensors
What is a characteristic of on-line gaming systems mentioned in relation to data volume?
Supporting millions of concurrent users
How has the scale of data storage evolved since 2000 based on the information provided?
$50$ times larger
What is characteristic of sensors embedded into everyday objects that contribute to big data?
They create billions of new, constantly-updated data feeds
Why do clickstreams and ad impressions capture user behavior at high event rates?
To reflect user behavior at millions of events per second
What is a key aspect of machine to machine processes mentioned in terms of data exchange?
Exchange among billions of devices
What impact do smart phones and sensors embedded into everyday objects have on data generation according to the text?
Result in billions of new, constantly-updated data feeds containing varied information
Explore the differences between k-means clustering and classification in machine learning. Learn about how classification is supervised learning with predefined classes, while clustering tries to group objects without labeled classes. Understand the key concepts of optimization criterion, feedback signal, and raw data in clustering.
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