Multiple-instance learning
Encyclopedia
Multiple-instance learning is a variation on supervised learning
. Instead of receiving a set of instances which are labeled positive or negative, the learner receives a set of bags that are labeled positive or negative. Each bag contains many instances. A bag is labeled negative if all the instances in it are negative. On the other hand, a bag is labeled positive if there is at least one instance in it which is positive. From a collection of labeled bags, the learner tries to induce a concept that will label individual instances correctly.
Multiple-instance learning was originally proposed under this name by , but earlier examples of similar research exist, for instance in the work on handwritten
digit
recognition
by .
Numerous researchers have worked on adapting classical classification techniques, such as support vector machines or boosting
, to work within the context of multiple-instance learning.
Supervised learning
Supervised learning is the machine learning task of inferring a function from supervised training data. The training data consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object and a desired output value...
. Instead of receiving a set of instances which are labeled positive or negative, the learner receives a set of bags that are labeled positive or negative. Each bag contains many instances. A bag is labeled negative if all the instances in it are negative. On the other hand, a bag is labeled positive if there is at least one instance in it which is positive. From a collection of labeled bags, the learner tries to induce a concept that will label individual instances correctly.
Multiple-instance learning was originally proposed under this name by , but earlier examples of similar research exist, for instance in the work on handwritten
Handwriting
Handwriting is a person's particular & individual style of writing with pen or pencil, which contrasts with "Hand" which is an impersonal and formalised writing style in several historical varieties...
digit
Digit
Digit may refer to:* Digit , one of several most distal parts of a limb—fingers, thumbs, and toes on hands and feet* Numerical digit, as used in mathematics or computer science* Hexadecimal, representing a four-bit number...
recognition
Optical character recognition
Optical character recognition, usually abbreviated to OCR, is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files, to computerize a record-keeping...
by .
Numerous researchers have worked on adapting classical classification techniques, such as support vector machines or boosting
Boosting
Boosting is a machine learning meta-algorithm for performing supervised learning. Boosting is based on the question posed by Kearns: can a set of weak learners create a single strong learner? A weak learner is defined to be a classifier which is only slightly correlated with the true classification...
, to work within the context of multiple-instance learning.