Computers and Technology, 11.06.2020 19:57 tamya12234
Extract kmeandata from cluster_data. mat as your dataset. a. Initialize the cluster centers (the means) at (-2,-2) and (4,4) b. Calculate the distance between each data point and each center (you should have an array containing a row for every data point and a distance value for each cluster mean). c. Assign each data point with the label of its nearest cluster (cluster_ind) d. Plot the clustered data points using different colors for each cluster e. Update the means f. Continue for 4 iterations, creating one plot for each iteration inside a 2x2 subplot. g. Repeat for a new initialization of cluster centers: (0, -1) and (-1, 4)
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Computers and Technology, 22.06.2019 14:20
Consider a byte-addressable computer with 16mb of main memory, a cache capable of storing a total of 64kb of data and block size of 32 bytes. (a) how many bits in the memory address? (b) how many blocks are in the cache? (c) specify the format of the memory address, including names and sizes, when the cache is: 1. direct-mapped 2. 4-way set associative 3. fully associative
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Jackson, who works in the finance department of a company, is holding a seminar for other employees on how to file taxes. only three employees sign up to attend the seminar. which device can he use to share his presentation with a group of three employees?
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Computers and Technology, 23.06.2019 23:30
What can you prevent issues related to downloading content form the internet
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Extract kmeandata from cluster_data. mat as your dataset. a. Initialize the cluster centers (the mea...
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