Traditional K-means has a number of limitations, such as sensitivity to outliersand difficulty in handling clusters of different sizes and densities, or with non-globular shapes. Comment on the ability of fuzzy c-means to handle these situations.

3. (6 pts) internally in the computer, with few exceptions, all numerical computation is done using binary numbers. output, however, often uses ascii, which is formed by appending 011 to the left of a bcd code. thus, an algorithm that directly converts a binary integer to a bcd integer is very useful. here is one such algorithm 1) draw lines to the left of the binary number to bound the expected bcd decades. (each decade is a group of 4 bits.) move the binary number one bit to the left. add 0011 to each bcd decade containing a binary value> 0100 repeat steps 2-3 until the last bit in the binary number has been moved into the least significant decade position. (note that when the last bit has been shifted into bcd decade, step 3 is not repeated.) read the bcd result. 2) 3) 4) 5) a) execute the algorithm for the binary number 1101101 b) execute the algorithm for the binary number 01110101110 4. (4 pts) represent the decimal number 3568 in bcd; excess-3 code; ascil; and hex.

What result from the passage of this amendment

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