Lesson 3 - Supervised learning Flashcards

1
Q

Supervised Learning formalization

A
  • Input: x∈X, X is the space of instances of the task
  • Output: y∈Y, changes depending on the task:
    • classification, binary
    • multi-class classification, natural numbers
    • regression, real numbers
  • we assume that an oracle exists
  • the training data is composed from historical records (x, y), generated by the oracle
  • an hypothesis is selected from an hypothesis space using training data
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2
Q

Types of oracle

A
  • Oracle deterministic
    • a function associates input and output
    • target function is deterministic and unknown
  • Oracle stochastic
    • input and output chosen according to a certain probability distribution
    • target function is stochastic and unknown
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3
Q

Training set

A

A series of pairs, generated according to a probability function

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4
Q

Empirical error/risk

A
  • error on training data
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5
Q

Ideal error/risk

A
  • expected error on a given pairs x, y drawn according to the probability distribution
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6
Q

Characteristics of the selected hypothesis

A
  • a plausible hypothesis is selected using training data
  • it should generalize well
    • correct predictions also for unseen examples
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7
Q

Inductive bias

A
  • assumptions made on hypothesis space and learning algorithm
    • hypothesis space cannot contaion all possible functions
    • how the space is explored
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