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Consider the data with categorical predictor x1 = {green or red} and numerical predictor x2 and the class variable y shown in the following table. The weights for a round of boosting are also shown in the table. Suppose the classifier built from this round of boosting assigns y = 1 for x2 < 0.45 and y = -1 for x2 > 0.45. Compute the coefficient α for this classifier in the adaboost algorithm.
Q. Explain Microcode and VLSI Technology? It is considered that CU of a computer be assembled using two ways; create micro-program which execute micro-instructions or construct
Volatility of memory: Non-volatile memory will received the stored information even if it is not continually supplied with electric power. It is appropriate for long-term
The Credit Line The Credit Line is a set of informational facts usually found below or beside a picture of a work of art. Should the picture appear in a book, magazine, poster,
Minimisation using Boolean algebra is not always straight forward and sometimes it is not obvious if a further manipulation would give a simpler circuit. Karnaugh maps are a muc
Discuss the role of handler’s classification?
An accessor is a class operation that does not change the state of an object in C++. The access or functions require to be declared as const operations
What are Multidimensional Arrays? Multidimensional array: Multidimensional arrays can be defined as "arrays of arrays". For example, a bidimensional array can be fictional as a
Algorithmic Complexity theory: Moreover a similar situation occurs in broad to specific ILP systems when the inference rules are deductive thus they specialize. So at some sta
Can we define our own Match Code ID's for SAP Matchcodes? Yes, the number 0 to 9 are reserved for us to make our own Match Code Ids for a SAP described Matchcode object.
Kirc hoff's Voltage Law The sum of all the voltage drops around a closed circuit loop will add to zero V1+(-V2)+(-V3)+(-V4)= 0
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