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One discrete problem that is expensive to solve on many computers is that of counting the number of bits that are set to 1 in a (binary) number, sometimes called the population function. For example, the decimal number "37" is "00100101" in binary, so it contains three bits that are set to binary "1". [7]: 282
The first row shows the possible p-values as a function of the number of blue and red dots in the sample. Although the 30 samples were all simulated under the null, one of the resulting p-values is small enough to produce a false rejection at the typical level 0.05 in the absence of correction.
More precisely, in multiple-instance learning, the training set consists of labeled "bags", each of which is a collection of unlabeled instances. A bag is positively labeled if at least one instance in it is positive, and is negatively labeled if all instances in it are negative. The goal of the MIL is to predict the labels of new, unseen bags.
Merton believed that it is multiple discoveries, rather than unique ones, that represent the common pattern in science. [4] Merton contrasted a "multiple" with a "singleton"—a discovery that has been made uniquely by a single scientist or group of scientists working together. [5] The distinction may blur as science becomes increasingly ...
One approach is multiple imputation by chained equations (MICE), also known as "fully conditional specification" and "sequential regression multiple imputation." [ 15 ] MICE is designed for missing at random data, though there is simulation evidence to suggest that with a sufficient number of auxiliary variables it can also work on data that ...
For example, each of 65,536 single-bit processors in a Thinking Machines CM-2 would execute the same instruction at the same time, allowing, for instance, to logically combine 65,536 pairs of bits at a time, using a hypercube-connected network or processor-dedicated RAM to find its operands.
One approach is to delimit separate words with a non-alphanumeric character. The two characters commonly used for this purpose are the hyphen ("-") and the underscore ("_"); e.g., the two-word name "two words" would be represented as "two-words" or "two_words".
Reverse lookup is a procedure of using a value to retrieve a unique key in an associative array. [1]Applications of reverse lookup include reverse DNS lookup, which provides the domain name associated with a particular IP address, [2]